The same recipe obtained in laboratory-scale equipment cannot, without modifications, generally be used to freeze-dry the product in a pilot-scale or industrial-scale freeze-dryer. This is because scale up does not guarantee that you will obtain the same dynamics of product temperature and ice content (i.e., the same primary drying length) as those at the laboratory scale. Product temperature can often exceed the limit value, and/or the length of the process can be different. 

Two of the main sources of the problem relate to the freezing and primary drying steps. The level of undercooling and, thus, nucleation can be different in the two apparatus, and heating conditions may also vary. In a laboratory freeze-dryer, heat is mainly supplied by radiation, and the large transparent window of a freeze dryer has a big influence. In these conditions, there is a small influence and relationship between shelf temperature and process evolution. This aspect is often overlooked, even if it can be evidenced quite easily. On several occasions I have seen presented data where the product temperature was higher than the shelf temperature, while the speaker was explaining the several trials conducted to improve the quality of the cake! As the process is endothermic, product temperature can be higher than shelf and fluid temperature only if heat is supplied by radiation.

The list of variables that have to be considered is quite long, but is summarised below: 

environmental conditions in the manufacturing area, which can affect nucleation as explained above

A large amount of literature has been published in this area (1–9). 

Up until now, the influence of pressure distribution over the shelves has been generally neglected, but is important in the case of small clearances (to increase the loading) and high sublimation rates. Finally, because of the strong effect the chamber pressure has on the process, pressure control must be similar and effective—higher impedance of the dryer can cause chocked flow conditions and, thus, uncontrolled and higher pressure in the chamber. Obviously, human errors such as using different types of pressure sensor, like a capacitance manometer and a Pirani gauge, with the same pressure set point, must be avoided. 

When it comes to freeze drying, the freezing and ice-nucleation steps are a concern, so any technology that can control nucleation will greatly improve the situation. Recently, a system based on rapid pressure reduction during cooling has been presented and seems very promising (10). Other systems are also under study. In particular, I believe that solutions based on ultrasound can become competitive if some mechanical problems are solved (11, 12). 

Up until now, much attention has focused on the scale up of the drying recipe. A survey of literature shows (3–9) that scaling up a freeze-drying recipe is an open problem. The PAT Guidance for Industry released by the FDA in 2004 emphasises the need for a deep understanding of biotech processes to improve manufacturing efficiency, with the goal of building product quality into the process. 

A first proposed approach to the problem was to design a robust recipe (or a robust design space) that could be used in both the lab-scale and pilot-scale freeze-dryer under the hypothesis that the two pieces of equipment are equivalent. In this case, no scale-up is actually carried out because the same recipe is used in different freeze dryers. The recipe that is used can be excessively conservative, and the procedure is based on a trial and error approach because it is hard to establish if the recipe is robust enough. 

Recently, some papers were published that consider process modelling (

). Process modelling is an important improvement, but the model was used as an accessory tool, without giving the requested answer in a simple way, as will be discussed later.  

Sidebar: Previous attempts to use moldelling in scale up.

A simple and effective methodology for recipe-scale-up and process transfer that takes into account the variation of product resistance during the main drying, as well as the possibility that product resistance may change between freeze-dryers, is now available, and is described in detail in the literature (1, 2). Such an approach involves using mathematical modelling to simulate product evolution for a selected recipe, as well as a few experiments to determine model parameters and to characterise different freeze-dryers. The effect of parameter uncertainty can be easily accounted for, as can batch non-uniformity. Differences in the cake resistance, a consequence of differences in ice nucleation, can also be easily accounted for, but it will be necessary to characterise the cake obtained in industrial equipment. 

Figure 1: Modification of the drying recipe (shelf temperature) passing from equipment 1 to equipment 2 for uniform batches: the same product temperature (TB) and the same ice thickness evolution are obtained.

 shows an example application of the proposed procedure. The red line is the new recipe that takes into account the higher heat transfer coefficient obtained in the industrial scale apparatus.

The usual tools to characterise lyophilisation formulations are differential scanning calorimeter analysis and the cryomicroscope, which provide the collapse temperature and the temperature of occurring transformations.

If we consider the lyophilisation system (the freeze-dryer and the vials containing the product), then the two parameters that fully characterise the system are the effective heat transfer coefficient between the shelf and vial bottom (K

) and the resistance to vapour flow of the dried cake (R

) The knowledge of these quantities enables us to use modelling tools for scale up, obtaining the design space and off-line optimisation. These two parameters are required by any predictive control algorithm and, for this purpose, are generally estimated by the monitoring system. In practice, the dependence of the heat transfer coefficient on the chamber pressure is desired, which necessitates a series of experiments (at least three, at different pressures) to be conducted. With regards to resistance to vapour flow, the dependence on cake thickness must be evaluated. Only in relatively rare cases is this dependence linear; usually, asymptotic behaviour is observed. For products where microcollapse can occur, and in particular with sugars at a low solid concentration, it may be necessary to evaluate cake resistance at different temperatures. Of course, the other variable that is important to monitor is the sublimation rate.

Methods using the pressure rise test are useful because they enable the K

 values to be determined in just one test, which only lasts a few seconds and does not require preliminary experiments. Different algorithms can be used [e.g., MTM (Manometric Temperature Measurent), DPE (Dynamic Parameters Estimation method), PRA (Pressure Raise Analysis)]: estimation is fast and can be conducted in-line. For control purposes, the accuracy is sufficient, although not perfect. The DPE+ algorithm directly measures the sublimation flux and provides a more robust estimation of the other parameters.

Another method that has been recently proposed is based on Tunable Diode Laser Absorption Spectroscopy (TDLAS). This technology uses Doppler-shifted near-infrared absorption spectroscopy to measure water vapour concentration and gas flow velocity in the duct connecting the freeze-drying chamber and condenser. The vapour mass flux can be calculated given an estimation of the velocity profile in the duct. This technique is interesting for measuring in-line sublimation flow and can speed up the experimental measuring campaign, even though its reliability is related to the correct estimation of the vapour velocity profile, which is not fully developed in practical conditions and is strongly dependent on the chamber conditions. Calculation of the parameters K

 is possible, but requires knowing the value of shelf temperature and of product temperature at the bottom and interface of sublimation, thus requiring additional experimental work to be applicable.

All these methods supply a batch average of the parameters. The only way to obtain the distribution of the variables of interest, and in particular the distribution of K

, is by gravimetric methods. However, this is very time consuming as it requires a drying cycle to be conducted and then stopped during primary drying. A large number of vials must then be weighed to evaluate the sublimation rate of each vial.

Figure 2: The special Lyo-balance by Politecnico di Torino, with the wireless temperature measurement system.Regarding cake resistance, this is related to the specific surface measured by BET adsorption techniques using inert gases (Argon), but it is not possible to estimate it based on this measurement. Similarly, it can be related to the average pore size, but cannot be estimated reliably from image analysis of the cake.

What is interesting, however, is the use of a special weighing device to estimate the value of R

 shows such a device, equipped with a wireless temperature sensor to measure, without bias, the temperature in the weighed vials, realised by Politecnico di Torino (Italy). The device allows the R

 curve to be determined in a single run for industrial apparatus. 

A detailed analysis of the different monitoring systems available for industrial processes, and of those proposed for laboratory use can be found in the literature (12–16).

) can strongly improve lyophilisation processes in several ways. My research team has recently published several papers demonstrating that predictive modelling is not only possible, but reliable and effective, and has developed dedicated software for major multinational companies to solve specific requests.

Figure 3: A graphical representation of the role of mathematical modelling in process monitoring, process control and apparatus design.

The first point to evidence is that modelling can be very useful, but only if the proper model is selected and developed, taking into account the allowed complexity and parameters that must be determined. Literature is rich of very detailed and accurate models, but a detailed model is not always a good model. The level of detail must be chosen according to the final use; for example, a model for predictive control will be different from a model for off-line optimisation. It must be stressed that the quality of the prediction generally depends more on the uncertainty connected with the parameters used, than on the complexity (and the dimension) of the model. The good engineering rule is that the model must be the simplest one that gives the requested accuracy.

A review of the different modelling approaches is available (17).

The second point is that modelling should supply the requested answer, and not just a lot of (perhaps interesting) data. To explain this concept, I will take the example of scale up. Recently a few papers were published that showed the use of modelling to address the scale up problem. In these cases, the model was used to supply predictions that helped to obtain the final recipe, but a lot of simulation work was required (together with experimental trials) because no direct answer was obtained. The straightforward approach, in my opinion, is to solve the "inverse problem": calculate the sequence of set points that enable you to obtain the required temperature history of the product. 

The subject is very wide, so I will limit myself to evidence from the field where predictive modelling has already been used with success, in particular for the development of sensors, for equipment design and optimisation, and for in-line and off-line process optimisation. In some cases, commercial products are already available or will become available soon (18).

Predictive modelling can be used to develop software sensors. These sensors combine a model with physical measurements to estimate variables that cannot be measured directly. This is particularly interesting in freeze-drying because the main quantities of interest (residual amount of ice, residual moisture in secondary drying) cannot be measured directly. One example of this technology is "smart vials" where a temperature measurement of the product, or even of the vial wall, can be transformed into an estimation of interface temperature, residual ice or heat transfer coefficient. Another monitoring software, that takes advantage of the measurement of the water desorption rate, enables the residual moisture in secondary drying to be estimated, without the need to extract any sample, and to carry out preliminary experiments.

Tools for parameter identification are also available; an example are the methods based on the pressure rise test (this is carried out closing the duct from the chamber to the condenser for a few seconds), where the use of improved methods based on process modelling extends the range of operation and improves accuracy, especially for evaluating the parameters necessary for process control and optimisation (19–22).

Equipment design can affect product quality and batch heterogeneity during operation (mainly during primary drying), through radiation, as well as through pressure gradients in the drying chamber and temperature gradients over the various shelves. The use of Computational Fluid Dynamics can be very effective, especially if dual-scale modelling approaches are adopted. When applied to the drying chamber, this approach can enable the variance of the batch to be estimated, and thus suggest the necessary modification of the design to reduce variance below a set value, or to estimate the influence of loading (and also of the clearance between shelves) to pressure drops. This allows also to evaluate whether the product uniformity is affected. Modelling can be used not only to improve the design of the drying chamber, but also that of the condenser and the selection of duct size and valves, which ensure the required performances. It is also possible to predict chocked flow conditions and, thus, the conductance of the apparatus (23).

Model-based tools enable the freeze-drying of a pharmaceutical formulation in a specific freeze-dryer to be optimised, thus minimising the duration of the process, as well as maintaining product temperature below a limit value to preserve product quality. This can be done either off-line, using the design space concept, or in-line, using a predictive control algorithm.

In fact, if a preliminary investigation determines model parameters (cake resistance and an effective heat transfer coefficient), it is possible to optimise the recipe off-line using a mathematical model of the process to build the design space of the formulation. With this approach, it is also possible to build a design space for each group of vials, to take into account batch heterogeneity, thus identifying the optimal operating conditions for the whole batch. Modification of the cake resistance during drying can also be taken into account. The procedure is explained in detail in the references (24–25) and has been tested in industrial cases. 

 shows an example for a placebo formulation.

Figure 4: Design space for a sucrose solution (5% w/w). The dashed line identifies the limit operating conditions nearby the endpoint of the drying, while the square symbol corresponds to the selected operating conditions. Isoflux curves (in kg h-1m-2) are shown. 

Using predictive control systems based on a simplified model can enable the development of an optimal freeze-drying cycle in a single run (12). For this purpose, it is necessary for sensors, such as those mentioned above, to supply both the status of the system and the value of the parameters of interest. A system of this type, which we have called LyoDriver (

) at the Politecnico di Torino, has been already developed and tested. The commercially available version makes use of the pressure rise test to monitor the process and, in particular, the DPE (26). A more sophisticated version takes advantages of the multivariate control approach (MPC) (27). Obviously, control algorithms can be used not only to develop optimal recipes, but eventually to automatically modify the recipe in a different piece of equipment. They can also control the process, rejecting disturbances and responding to undesired modification of the set point, thus avoiding product failure (28).

Figure 5: The LyoDriver concept, developed by Politecnico di Torino for Telstar s.a.(Spain); the chamber of a LyoBeta freeze-dryer, used for recipe development is shown, together with a monitored pressure rise and the screenshot of the software. 

Finally, process transfer or scale-up can be made easier and more robust either using specific software after a process identification step or a software tool that can estimate in real time the consequences of process off-sets.

The vials in the chamber of the freeze-dryer can exhibit different dynamics, resulting in intra-shelf variance and inter-shelves variance, which generally may be even larger. The causes, however, may differ. Even in a freeze-dryer that guarantees uniform operating conditions, the cake structure can be different because ice nucleation phenomenon is a stochastic event that may result in ice crystals of differing size, in a different resistance to mass transfer, and finally in a different drying kinetics and temperature profile. This phenomenon can be very pronounced in some limit cases, with freezing occurring over a long time interval and, thus, with very different supercooling for the different vials, which can be reduced only by utilising a device that controls nucleation.

Other causes of variance are radiation from the wall of the chamber, temperature gradients on the heating shelf, vapour fluid dynamics and non-uniform inert distribution (29).

Many factors contribute to significantly different heat transfer rates in the vials of a batch, such as the shape of the bottom of the vial, which affects the heat transfer from the fluid in the shelves to the product, the contact between the vials, and the radiation from the chamber walls and the chamber door. These effects can be minimised, improving the equipment design and reducing tolerance in vial manufacture.

Another significant cause of inter-vial variance is the fluid dynamics of the sublimating vapour inside the lyophilisation chamber. This effect can be efficiently investigated by using computational fluid dynamics, which evidences the influence of some geometrical parameters of the drying chamber (clearance between the shelves and position of the duct between the chamber and the condenser). The pressure gradients inside the chamber are important because the product temperature depends on the pressure (i.e., the higher the vapour pressure, the higher the product temperature) and, thus, represent a source of batch unevenness. Of course, irregular positioning of the stoppers can also be a cause of variance, affecting the total resistance to vapour flow and the product temperature.

Estimating variance is necessary to select a proper safety factor for the shelf temperature set point in order to avoid collapse or scorch in some vials that experience higher temperatures—to avoid collapse in vials that have a higher residual moisture content due to slower drying (or melting in case of residual ice), as a consequence of earlier transition to secondary drying step. The apparently strange phenomenon for which, in some productions, collapsed products are observed in vials in different position in the batch, without an apparent reason, can be simply attributed to the casual combination of different effects (cake resistance, gap at the vial bottom, temperature gradients on the shelf) in case the recipe has very low safety margins.

Different sublimation rates over the shelf can be easily measured by stopping a freeze-drying cycle and weighing a sufficient number of vials; an example of this type of experimental results is shown in the 

. From these results, it is then possible to evaluate, for example, the distribution of the heat transfer coefficients and its average value and variance.

Figure 6: Sublimation rate variance over a shelf (half of the shelf is shown) and corresponding distribution of the effective heat transfer coefficients.

It is also possible to predict the behaviour of single vials in a batch, evaluating the effect of hydrodynamics, radiation and shelf temperature gradients. A dual-scale model is required for this purpose because it couples a 3D-model, describing the fluid dynamics in the chamber, and a second mathematical model, either mono- or bi-dimensional, describing the drying of the product in the vials. Different mathematical approaches are possible, as described in detail (18, 23). 

 shows a conceptual scheme, with the two-way coupling of a CFD model and a one-dimensional model of the vial, which enables the evolution of the temperature variance of the product to be predicted over two different shelves: on the left a uniform batch obtained on a bottom shelf, on the right the variance over the shelf close to the duct, where strong pressure gradients were observed. The use of such a modelling tool can predict the expected variance with selected operating conditions, including the number of shelves, as well as the clearance between vial and upper shelf, and the stochastic variability of the cake resistance.

The variance of the batch, however, cannot be easily measured during the process, especially in industrial apparatus, but it is possible, using the soft-sensor described earlier to estimate the variables of interest in several vials placed in different position over the shelf. 

Figure 7: The dual-scale approach and the interactions between the CFD and the one-dimensional model: the pressure distribution in an industrial scale apparatus (courtesy of Telstar, Spain) and the temperature profile with the interface temperature and sublimation flux evolution are shown. In the lower figure the variance of the product temperature for the vials on the 1st (l.h.s.) and on the 12th (r.h.s.) shelf during the freeze-drying of 5% solution of Bovine Serum Albumin.  

Even if is not an easy task, it is possible to improve the control system to manage heterogeneous batch. Two strategies can be followed. 

The first involves monitoring in-line not only the average state of the batch, but also that of the edge vials characterised by a higher product temperature, and choosing the best heating strategy according to their state. A hybrid system can be realised: the DPE algorithm can be coupled with a system that estimates the variance of the batch using sensors that monitor the single vials, and the control system can calculate the control actions on the basis of the mean product temperature and of the temperature of the radiated vials.

A different strategy is to track the dynamics of vials placed in different positions of the batch by using the model previously validated, and thus to estimate the batch variance for certain operating conditions. This information can then be used to set the tuning parameters of the controller in such a way that it chooses the best control strategy to meet the product specifications of all the vials.

1.	Fissore D., Pisano R. and Barresi A.A., 2010, A rational approach to process transfer and scale up in freeze-drying of pharmaceutical products. Drying 2010 - Proceedings of 17th International Drying Symposium (IDS2010) (E. Tsotsas, T. Metzger, M. Peglow, Eds.), October 3-6, Magdeburg, Germany, Vol. C, pp. 2178-2185. [ISBN: 978-3-86912-036-2]

2.	Fissore D., Barresi A.A., 2011, Scale-up and process transfer of freeze-drying recipes. Drying Technol., in press. 

3.	Jennings T.A., 2002, Transferring the lyophilization process from one freeze-dryer to another. American Pharmaceutical Review 5, 34-42. 

4.	Rambhatla S.; Pikal M.J., 2003, Heat and mass transfer scale-up issues during freeze drying: I. Atypical radiation and the edge vial effect. AAPS PharmSciTech, 4, Article 14. 

5.	Rambhatla S., Ramot R., Bhugra C., Pikal M.J., 2004, Heat and mass transfer scale-up issues during freeze drying: II. Control and characterization of the degree of supercooling. AAPS PharmSciTech, 5, Article 58. 

6.	Rambhatla S., Tchessalov S., Pikal, M.J., 2006, Heat and mass transfer scale-up issues during freeze drying: III. Control and characterization of dryer differences via operational qualification tests. AAPS PharmSciTech, 7, Article 39. 

7.	Sane S.V., Hsu C.C., 2007, Strategies for successful lyophilization process scale-up. American Pharmaceutical Review, 10, 132-136. 

8.	Mungikar A., Ludzinski M., Kamat M., 2009, Evaluating functional equivalency as a lyophilization cycle transfer tool. Pharmaceutical Technology, 33, 54-70. 

9.	Jo, E., 2010, Guaranteeing a quality scale-up. Pharmaceuticals Manufacturing Packing Sourcer, 49, 62-28.

10.	Konstantinidis A.K., Kuu W., Otten L., Nail S.L., Sever R.R., 2011, Controlled nucleation in freeze-drying: Effects on pore size in the dried product layer, mass transfer resistance, and primary drying rate, Journal of Pharmaceutical Sciences, 100, 3453–3470.

11.	Passot S., Trelea I.C., Marin, M., Galan M., Morris G.J., Fonseca F., 2009, Effect of controlled ice nucleation on primary drying stage and protein recovery in vials cooled in a modified freeze-dryer. J Biomechanical Engineering, 131,1-5. 

12.	Fissore D., Barresi A.A., 2011, In-line product quality control of pharmaceuticals in freeze-drying processes, in “Modern Drying Technology Vol. 3: Product Quality and Formulation”, (E. Tsotsas and A.S. Mujumdar, Eds.), Chap. 4. Wiley-VCH Verlag GmbH + Co. KGaA, Weinhein, pp. 91-154. [ISBN 978-3527-31558-1]. 

13.	Barresi A.A., Pisano R., Fissore D., Rasetto V, Velardi S.A., Vallan A., Parvis M., Galan M., 2009, Monitoring of the primary drying of a lyophilization process in vials. Chemical Engineering and Processing, 48 (1), 408-423. [DOI: 10.1016/j.cep.2008.05.004]. 

14.	Fissore D., Pisano R., Rasetto V., Marchisio D.L., Barresi A.A., Vallan A., Corbellini S., 2009, Applying Process Analytical Technology (PAT) to the lyophilization process. Chimica Oggi/Chem. Today 27 (2, Supplement “Focus on Analytical technologies), VII-XI. 

15.	Fissore D., Pisano R., Barresi A.A., 2011, On the methods based on the Pressure Rise Test for monitoring a freeze-drying process. Drying Technology, 29 (1), 73-90. [DOI: 10.1080/07373937.2010.482715] 

16.	Barresi A.A., Fissore D., Pisano R., 2011, Heat transfer in freeze-drying apparatus, in ”Heat Transfer / Book 1 (M.A. dos Santos Bernardes, ed.)”, Intech [ISBN 978-953-307-317-0], in press. 

17.	Velardi S.A., Barresi A.A., 2008, Development of simplified models for the freeze-drying process and investigation of the optimal operating conditions. Chemical  Engineering Research and Design, 86(1), 9-22. [DOI: 10.1016/j.cherd.2007.10.007] 

18.	Barresi A.A., Fissore D., Marchisio D., 2010, Process Analytical Technology in industrial freeze-drying, in: "Freeze-Drying/Lyophilization of Pharmaceuticals and Biological Products, 3rd rev. Edition" (L. Rey and J. C. May, Eds.), Chap. 20. Informa Healthcare, New York, pp. 463-496. 

19.	Barresi A.A., Velardi S.A., Pisano R., Rasetto V., Vallan A., Galan M., 2009, In-line control of the lyophilization process. A gentle PAT approach using software sensors. International Journal of Refrigeration, 32, 1003-1014. [DOI: 10.1016/j.ijrefrig.2008.10.012] 

20.	Velardi S.A., Rasetto V., Barresi A.A., 2008, Dynamic Parameters Estimation method: advanced Manometric Temperature Measurement approach for freeze-drying monitoring of pharmaceuticals solutions. Industrial Engineering Chemistry Research, 47(21), 8445-8457. [DOI:10.1021/ie7017433] 

21.	Fissore D., Pisano R., Barresi A.A., 2011, On the methods based on the Pressure Rise Test for monitoring a freeze-drying process. Drying Technology, 29 (1), 73-90.  [DOI: 10.1080/07373937.2010.482715] 

22.	Fissore D., Pisano R., Barresi A.A., 2011, Monitoring of the secondary drying in freeze drying of pharmaceuticals. Journal of Pharmaceutical Science, 100 (2), 732-742. [DOI: 10.1002/jps22311] 

23.	Rasetto V., Marchisio D.L., Fissore D., Barresi A.A., 2010, On the use of a dual-scale model to improve understanding of a pharmaceutical freeze-drying process. Journal of Pharmaceutical Science, 99 (10), 4337-4350. [DOI: 10.1002/jps.22127] 

24.	Giordano A., Barresi A.A., Fissore D., 2011, On the use of mathematical models to build the design space for the primary drying phase of a pharmaceutical lyophilization process. Journal of Pharmaceutical Science ,100 (1), 311-324. [DOI: 10.1002/jps.22264] 

25.	Fissore D., Pisano R., Barresi A.A., 2011, Advanced approach to build the design space for the primary drying of a pharmaceutical freeze-drying process. Journal of Pharmaceutical Science, in press (available on-line) [DOI 10.1002/jps.22668] 

Articles

Special Feature

The same recipe obtained in laboratory-scale equipment cannot, without modifications, generally be used to freeze-dry the product in a pilot-scale or industrial-scale freeze-dryer.

Overcoming Common Lyophilization Scale-Up Issues

Mark Shon. VP of Sales and Marketing for SP Scientific.Ideally, all product formulations should experience the same conditions when it comes to lyophilisation as this leads to final product homogeneity. In practice, however, nucleation can occur. Nucleation is a random process and has proven difficult for the industry to control. During the freezing stage, some vials may nucleate close to the thermodynamic freezing point of the formulation (e.g., -3 ∘C), while others may nucleate at -20 ∘C or lower much later in the freezing step. Consequently, all the vials will behave somewhat differently because the temperature at which nucleation occurs ultimately determines the resistance to the water vapour flow out of the frozen sample during freeze drying. The lower the temperature when nucleation occurs, the longer the cycle time. Many other adverse effects have also been attributed to uncontrolled nucleation (

Table 1: The effects of uncontrolled nucleation.A number of techniques for controlling nucleation have been previously described, including the ice fog technique and ultrasound.(1,2) One technique that could offer potential for controlling nucleation is a technology developed by Praxair Inc (ControLyo) that enables ‘nucleation on-demand’. The technique involves cooling vials to a temperature at which nucleation can occur and then pressurising the system with nitrogen or argon gas. The freeze dryer is then rapidly de-pressurized and all vials nucleate simultaneously. The benefits include reduced cycle times, improved homogeneity of product, less damage from freezing, reduced vial breakage and an overall process that is generally more in conformity with quality by design initiatives. In addition, the technology is repeatable, scalable and has a large body of documented experimental data to validate its efficacy and benefits.(3)

In the initial work conducted by Praxair, they demonstrated controlled nucleation in freeze dryers as large as 5 m2. In a drying time optimisation experiment conducted by Praxair in collaboration with Baxter BioPharma Solutions, primary drying time was reduced 41% in the controlled compared with the uncontrolled nucleation run.3 Given the cost of freeze drying, cycle time reduction is a critical goal in the industry. Praxair has now implemented the technology on larger production freeze dryers. The hurdle is probably not the scalability of the technology, but the time and cost of a manufacturer having to revalidate an entire process once the technology has been incorporated. Because of this, the technology may be more practical for a new drug formulation where validation has yet to be performed.

There is significant data that clearly show the benefits of controlled nucleation,4 but most of these have been generated using development freeze dryers.  The real commercial benefit of any technology will come when it is adapted for production freeze dryers.  Controlling nucleation will also benefit biological products. We have conducted work with lactate dehydrogenase and human growth hormone, which are both sensitive proteins. Controlled nucleation led to less protein aggregation and greater stability and function of the proteins after lyophilisation.

1. S. Rhambhatla et al., AAPS Pharm. Sci. Tech., 5(4), e58 (2004).

2. A. Hottot, K. Nakagawa and J. Andrieu, Chemical Engineering Research and Design, 86(2), 193–200 (2008).

3.Data held on file at Praxair and SP Scientific.

4. R. Sever, CPPR Freeze-Drying of Pharmaceuticals and Biologicals Conference (Garmisch, Germany, 2010).

Ideally, all product formulations should experience the same conditions when it comes to lyophilisation, but in practice, however, nucleation can occur.

Controlling Nucleation

James Drinkwater is Process and Compliance Director at Bioquell UK and independent Chairman of the Pharmaceutical and Healthcare Sciences Society - PHSS. James Drinkwater is also a member of the PHSS freeze dryerâlyophilisation special interest group. The increase in aseptic processing driven by the growing number of biologically-derived products has led to an increase in freeze-drying applications in this area at both research and production scales. Sterilisation by steam (or moist heat) is the accepted and, to date, preferred option for the biological decontamination of a lyophiliser. This traditional method has a number of advantages: 

a proven and regulatory accepted technology

validation methodologies are well developed and accepted

no potential for chemical impact on biological products

limited impact from process residual water.

However, the process is not without its problems. The process generates residual heat and requires cool-down time ahead of the freeze-drying process—cool down times can be long because of material thermal mass. The pressure and thermal cycling also stresses the freeze dryer such that significant and robust (and often expensive) engineering is required, in addition to robust seals that have to operate in two contra directions. Pressure vessel codes require more significant design input, as well as qualification and certification, which increases project execution times, complexity and costs. And developments or alterations require significant requalification because these pressure code ratings may change. Finally, such a sterilisation process (and the clean steam generation plant and delivery system required) may be impossible to retrofit to existing lyophilisers built without a decontamination facility; product and process development today require such upgrades to have a validated biological decontamination process. Because of these challenges, there has been considerable interest in alternative decontamination methods.

One alternative decontamination method is to use hydrogen peroxide (H202 ). Although not yet widely used, H202  is a long-established method for surface biological decontamination. Validation methodologies are also well established, although the process is under more regulatory scrutiny than well-accepted, traditional steam sterilisation. Using the H202  method, it is possible to validate surface sterilisation with a sporicidal log reduction (SLR) of 6-log with Geobacillus stearothermophilus biological indicators (1). 

H202 vapour  also offers several other advantages:

The process uses ambient temperature process, so there is no residual heat impact to freeze-drying.

Stressing is significantly reduced. Vacuum design is the main design requirement and there is no need for pressure vessel coding.

Sealing integrity is not as challenging as with steam sterilisation.

Vapour phase H202  generators are significantly lower cost and feature less complex engineering compared with clean steam generators.

If an isolator or restricted access barrier systems (RABS) offload barrier is decontaminated with H202 vapour , there is no timing issue between when the barrier and lyophiliser are decontaminated because they can be done at the same time. With steam sterilisation, the hot door prevents simultaneous decontamination of the offload barrier.

Vapour phase H202  surface treatment is usually applied to indirect product contact parts. Surface sterilisation is achieved by a gassing-in-place (GIP) process. In aseptic filling operations, separating potentially contaminating operators from sterilised parts is a significant risk mitigation issue. Using GIP for indirect product contact parts (e.g., cap/stopper feeder bowls that have an indirect route of bio-contamination transfer to products) enables operator separation to be maintained once the surface has been sterilised (2). 

When it comes to lyophiliser sterilisation, H202  offers several benefits. However as there is significant air turbulence during the lyophilisation process, as well as open, exposed product the lyophiliser surfaces may be considered indirect product contact. Such critical surfaces must be validated for surface sterilisation but also if chemical agents are used then verification that the decontamination process is residue free to prevent potential of transfer to sensitive products is important. The regulatory acceptance for GIP, using vapour phase H202 , as a surface sterilisation, residue free process could translate to lyophilisers, and has recently received international regulatory approval. 

Additionally, because H202 vapour  uses ambient pressures, it eliminates any issues relating to the design of pressure vessel codes. It also significantly lessens the difficulties relating to integrity via pressure and thermal cycling. However, it should be noted that for full lyophiliser surface biological decontamination, H202 vapour  requires a vacuum transfer method to assure decontamination of connection dead legs. Using this method, together with buffer systems, standard H202 vapour generators can be used, which optimises design, integration and cost. Lyophilisation cycle times can also be optimised because there are no undesirable thermal loads (from a previous sterilisation process) at the start of the freeze-drying processes.

Steam sterilisation is a well-established and GMP-compliant process suitable for sterilising porous loads, and will remain the preferred method over other alternatives until new processes are fully developed. H202 vapour , as with any new process, has several drawbacks, such as:

Until widespread acceptance, the process will be under more regulatory scrutiny

Clean-in-place heat residuals can impact on H202  vapour decontamination. This issue requires further study, and greater monitoring and control

End point study for gas residuals needs to be controlled to ensure that biological products are not exposed to oxidising agent residuals

Vapour is poor at passive diffusion. Vacuum transfer methods are required to decontaminate dead leg connections (typically up to six pipe work diameters).

As a chemical-oxidising, free-radical attack-kill process, hydrogen peroxide bio-decontamination requires process compatibility studies to assure both effective 6-log SLR bio-decontamination and prevention of chemical impact on products (particularly biological based). 

Extra study is also required for cycle optimisation, biological efficacy assurance and product compatibility in the following areas: 

heat residuals from any clean-in-place process ahead of the H202 process

chemical compounding of cleaning agent residuals with H202  and possible chemical transfer to product (not an issue with the water-for-injection cleaning step)

water residuals in the lyophiliser chamber and condenser that potentially compound with H202  and impact efficacy. 

end-point residuals of H202  that may impact via oxidisation on biological products. Additionally, until the implementation of Quality Risk Management (QRM), the automated gaseous vapour phase H202  bio-decontamination process was not developed for GIP of indirect product contact parts and under specified conditions accepted by regulators to achieve surface sterilisation. Also, without closure of the research issues on water residuals in the Condenser and verification that H2O2 will not contaminate products, it is not enough to just prove biological decontamination efficacy.

Ongoing research and work is taking place to further develop and improve H202  decontamination processes, however, and it is becoming a viable option. H202 , under specified conditions, is very capable of achieving surface sterilisation conditions. Compared with steam sterilisation, the daily costs are also lower, which is an important consideration given the increasing need to reduce manufacturing costs. 

Research-scale lyophilisers using vapour phase H202  could pave the way for integrated hydrogen peroxide generators or retrofitted systems that do not require steam generators. Once proven, the application can be scaled up to production size units. Because the H2O2 process is based on vacuum backfill of the decontamination vapour whatever the size of lyophiliser it is just the back fill rate that is variable hence fully scalable. Applying the same process at research and production scale reduces any possible issues during process scale-up transfer.

Biological Indicators for Gas and Vapor-Phase Decontamination Processes: Specification, Manufacture, Control and Use

 (PDA Technical Report 51, November 2010)

2. Restricted Access Barrier Systems — RABS (Pharmaceutical and Healthcare Sciences Society, November 2010)

The increase in aseptic processing driven by the growing number of biologically-derived products has led to an increase in freeze-drying applications in this area at both research and production scales.

The Decontamination Challenge

Switzerland is an important power in Europe's pharmaceutical industry. As well as being one of the EU's major trade partners, Switzerland represents an important source of new pharmaceutical innovation and is home to two of the world's largest pharma companies.

When it comes to Europe, most attention focuses on the EU pharmaceutical market and the R&D activity of companies in the 27 member states. Switzerland is not an EU member state, but remains one of Europe's most important pharmaceutical markets, as well as a major centre for medical research and new products. In 2010, the Swiss pharmaceutical market was valued at SF4.9 billion (€4 billion), which represented a 3.4% increase compared with the previous year (1). The country's healthcare spending represents 10.7% of gross domestic spending, which is one of the highest levels in the world. Per capita, pharmaceutical expenditure is around the average for Organisation for Economic Co-operation and Development (OECD) countries (2), but the country holds a particular interest for the pharma industry because there tends to be a high share of out-of-pocket payment (around 30%) both for total healthcare expenditure and pharmaceutical spending (2).  

Switzerland is ranked by the European Federation of Pharmaceutical Industry Associations as the fourth highest for R&D expenditure in Europe, behind the UK, France and Germany (3). The country's pharmaceutical industry has been active since the 19th century and is a great source of national pride. Traditionally, the country's lack of natural resources forced it to turn to innovative industries and build up an export network. Furthermore, it has been keen to attract foreign workers, whose presence is often viewed as having helped drive its R&D-based sectors (4, 5). Since 2007, work and residency conditions for EU citizens have been substantially relaxed (5). 

Although there has been a steady drift of R&D investment from Europe to the US since 2000, Switzerland's pharma industry has remained an important contributor to the country's economy. In 2011, its annual pharmaceutical exports were estimated to exceed $40 billion (€27.3 billion) (6), while the balance of pharmaceutical trade is positive and has continued to increase since 2000. The Swiss pharmaceutical industry is also a major source of employment, comprising approximately 35000 workers and supporting nearly 120000 other employees in related and downstream sectors (3, 7). For every new job created in the Swiss pharmaceutical industry, it has been estimated that a further two are generated elsewhere in the Swiss economy (8). 

For most Swiss companies, exports are a vital source of revenue, particularly as the growth of the domestic pharmaceutical market has been affected by government pressure to control prices. Another trend that is limiting the market for branded products is the steady growth of the country's genericdrug sector. In the past, there was little interest in generic products—possibly because of Switzerland's leading role in developing new medicines, which created brand loyalty among domestic consumers. In 2008, generics represented only about 9% of the Swiss national market, but estimates for 2011 suggest that generics now account for 12% of the market (2, 3). 

Switzerland is the home country of pharma giants Novartis and Roche, as well as a host of small and medium-size enterprises (SMEs). All the major multinational pharmaceutical companies are represented in the national market, but the leading forces, by far, are Novartis and Roche. Although active in 140 countries worldwide, Novartis maintains a strong link to its home country and employs approximately 12500 staff in Switzerland. Since 2008, Novartis has also been named in an annual survey of Swiss science university students as the most desired company to work for (7). Out of Novartis' estimated €5.1 billion annual R&D budget, approximately 56% is spent in Switzerland (7, 9). Meanwhile, Roche employs around 10000 people in Switzerland, which represents 12% of its global workforce (7). On a global basis, the company spends around €1.9 billion on R&D annually (9). In 2009, Roche strengthened its worldwide position through a US$47 billion takeover of Genentech. The merged group became the seventh largest drug company in the US market. 

From time to time, there has been speculation regarding a merger between Novartis and Roche. In 2003, Novartis announced that it had accumulated enough stock in Roche to control 32.7% of the company's voting rights; however, members of Roche's founding family spoke strongly against any merger, while Novartis' CEO stated that the company was not looking to launch a hostile takeover (10). Since then, rumours have periodically resurfaced, but Novartis has not made any overt move for Roche. In March 2011, one of the members of Roche's founding family left the Roche family voting group, reducing its stake in the company from 50.01% to 45.01%. Some analysts have predicted that, in the long term, a merger with Novartis would be attractive based on the companies' shared interest in oncology. However, Roche has issued a number of media statements to dismiss this possibility and claimed that the suitability of such a merger is even less logical than it was in 2003 (11). Roche's spokesman argued that while Roche has focused on personalised medicine and diagnostics, Novartis has diverged into generic drugs and eye care. 

Switzerland's regulatory agency is called Swissmedic and is based in Bern. Although Swissmedic is linked to Switzerland's Federal Department of Home Affairs, it is independent and has its own budget and, as with many other regulatory agencies, it is funded from the fees it charges for regulatory applications and payments from the government for public services.  

The agency cooperates closely with foreign agencies, including the EMA. Indeed, the EMA has had a mutual recognition agreement in place with Switzerland since 2002 (12). In principle, the agreement is to avoid duplication of procedures when Swiss and EMA requirements are deemed equivalent, but the nature of acceptable processes is frequently updated. In 2010, the EMA and Swissmedic updated their agreement regarding GMP inspection and batch certification to account for advanced therapy medicinal products, such as those in the field of transplants. This update was made because new regulations on advanced therapy medicinal products had separately come into force in the EU and Switzerland since 2007, but had not been considered in the context of the original mutual recognition agreement (12). The 2010 discussions between the agencies were designed to close any loopholes and avoid potential, regulatory misunderstandings regarding these types of products. The original agreements state the equivalence of the two GMP systems, so that a manufacturer in the EU or in Switzerland can release a batch of medicinal product for sale or supply into the market of either party. Although the agreement does relax some of the requirements for operating in the other market, manufacturers must still have an effective batch-recall system to ensure that products can be recalled at any time when so required (12).  

Another example of the two agencies cooperating on an area of mutual interest was during the 2009 H1N1 influenza pandemic. This collaboration was renewed in February 2011, with the two agencies agreeing to share confidential information about the authorisation and safety of medicines used in the context of H1N1 pandemic influenza. 

Swissmedic's work covers registration and approvals, but it is the Swiss federal government that decides on the maximal allowable public price for drugs in the country. This price is calculated from the ex-factory manufacturer price, distribution costs and a valueadded tax rate of 2.5% (2). The Federal Office of Public Health (FOPH) is the final decision-making body for pricing and reimbursement of approved drugs. The FOPH bases its decisions on product cost-effectiveness and also benchmarks prices with those in Germany, the UK, Denmark, the Netherlands, France and Austria. If the FOPH gives a positive reimbursement decision, then a drug is listed in a positive drug list called the Spezialitätenliste within 30 days. The pricing and reimbursement status of drugs is reviewed every three years and after patent expiry, but drugs that are considered particularly innovative can receive a discretionary additional 20% price reward (2). From 2012, generics can also be included in the Spezialitätenliste, if their ex-factory price is 10–60% lower than the Swiss reference product after patent expiry. 

Being one of the EU's major trade partners, Switzerland is a huge force in the European pharmaceutical market. In 2010, 41.5% of EU pharmaceutical imports came from Switzerland (3), which means that the performance of the Swiss pharmaceutical industry has a strong bearing on what happens to the pharmaceutical sector in the rest of Europe.

1. Swissinfo, "Cheaper Prices Slow Down Pharma Market Growth" (Switzerland), 

2. International Society for Pharmacoeconomics and Outcomes Research (ISPOR), "Switzerland–Pharmaceutical" (NJ, USA), 

3. EFPIA, "The Pharmaceutical Industry in Figures" (Belgium), 

4. SGCI Chemie Pharma Schweiz, "Die schweizerische chemisch-pharmazeutische Industrie" (Switzerland), 

, "Switzerland Relaxes Immigration Laws for Most European Nations" (Location of publishing source, 2007), 

6. Espicom, "The Pharmaceutical Market: Switzerland" (Chichester, UK, March 2011). 

7. Novartis, "Novartis en Suisse"  (Switzerland), 

9. G. Roth, "2010 Top 20 Pharmaceutical Companies Report," Contract Pharma,  online, 

www.contractpharma.com/contents/view/33747

10. A. Langley, "Novartis's Stake in Roche Fuels Merger Speculation," 

11. "Roche Changes Raise Novartis Takeover Question," Inpharm  online, 

12. EMA, "Switzerland. European Medicines Agency" (UK), accessed 8 June 2011). 

Industry Insider

Switzerland is an important power in Europe's pharmaceutical industry.

Swiss Pharma Strength

Product degradation is often overlooked compared with other supply chain issues. but if left unchecked can lead to the market entry of substandard medicines, whether through ignorance or gross negligence.

When it comes to discussions about supply chain vulnerabilities, counterfeit drugs are front and centre for good reason. According to estimates from The World Health Organisation, up to 30% of drugs sold in Africa, Asia and Latin America are fake and the International Policy Network reports that more than 700000 people die each year from counterfeit malaria and tuberculosis drugs alone (1). Counterfeits also impact pharmaceutical companies, which are losing as much as $75 billion in business each year (2).  

However, there is another serious threat to the supply chain that is often overlooked: pharmaceutical degradation. Degradation, as with counterfeiting, enables substandard drugs to fall into the hands of patients and is most prevalent in developing countries where inadequate storage facilities are commonplace and proper regulatory oversight is often lacking. Unlike counterfeiting, however, degradation is not solely the result of malicious activity and can stem from a variety of issues. There is no effective method for monitoring what occurs between point A and point B in the supply chain, but the main contributors tend to be humidity, temperature and expiration.  

In developing countries, materials often degrade because of shifts in temperature and humidity. This can occur during transport; for instance, storage containers offloaded at the port of entry may sit in the tropical sun for an extended period of time while waiting to clear customs.  

The transportation phase is not the only culprit. Following delivery, pharmaceuticals are frequently stored in warehouses that lack a suitable air conditioning system. The US Centers for Disease Control and Prevention estimate that 17–37% of providers expose vaccines to improper storage temperatures (3), which can diminish the levels of a drug's active ingredient or alter the excipient matrix and, ultimately, hinder its effectiveness.  

The concept of monitoring expiration dates seems fairly rudimentary. However, drugs that have passed their expiration date still frequently make it into the supply chain. This could happen as a result of ignorance, with the retailer being unaware that the expiration date had passed before delivery. The more common reason, however, is gross negligence where retailers repackage and re-label pharmaceuticals before putting them back into the supply chain. This is most prevalent in countries lacking sufficient regulation and where drugs are often sold at markets. To a lesser degree, repackaged drugs are also an issue in Europe because of parallel trade, where drug repackaging is legal. In these instances, there is no way to know how old a product is unless it is properly tested.  

In many regions it is difficult to consistently monitor the factors that can influence drug degradation, but technology can help pharma manufacturers, distributors and others involved in the supply chain to screen products to determine if they are potentially substandard.  

One of the most common technologies used today — besides laboratory testing — is the Global Pharma Health Fund's Minilab, which is used across 70 countries worldwide and leverages four types of tests to identify poor quality products. Pharmaceuticals containing less than 80% of the API will not pass the test. At just under $10000, Minilabs are relatively affordable, but require potable water, electricity and a conditioned-controlled environment where the testing is conducted.  

Another option is spectroscopy, which has gained considerable momentum since becoming available in portable, handheld instruments. There are several technologies that use spectrometry, but I will focus on infrared (NIR) and Raman spectroscopy in particular because these techniques exist in handheld formats and don't require contact with a sample. 

NIR is a well-known spectroscopic technique that measures molecular vibrations to identify individual chemical components of a drug or raw material. NIR requires an investment of manpower to create and maintain robust material libraries, but provides quick, reliable results once properly installed. It also has the advantage of not requiring contact with a sample. Compared with Raman spectroscopy, however, it has the disadvantage of being less selective and of requiring more up-front development work to build robust reference libraries. 

Raman spectroscopy is less well known than NIR, but is becoming more popular because it is available as a portable, handheld instrument. These instruments can be used essentially by anyone because they quickly identify chemical components without coming into direct contact with the substance. In other words, handheld instruments can scan through sealed glass, plastic bottles, bags and blister packs at ports of inspection or any other place in the supply chain using a laser that illuminates a sample and measures the molecular shift. Handheld Raman spectroscopy is currently being used by a number of large pharmaceutical manufacturers, as well as regulatory bodies worldwide. 

Pharmaceutical degradation may not have the visibility of counterfeiting, but it still poses a potential threat to patients and must be considered by pharma companies. Technology, however, can help ensure that substandard materials are removed from the supply chain and kept out of the hands of patients. Handheld Raman instruments represent a simplistic solution.  

is vice president of Thermo Scientific's Portable Optical Analysis business unit. 

1. J. Harris, P. Stevens and J. Morris, Keeping it real: combating the spread of fake drugs in poor countries (International Policy Network, May 2009). 

2. P. Gumbel, "How to Stop the Counterfeit-Medicine Drugs Trade", 

3. FiercePharma Manufacturing, "Potency drops investigated in H1N1 vaccines" (January 2010). 

Supply Chain

Product degradation is often overlooked compared with other supply chain issues, but if left unchecked can lead to the market entry of substandard medicines, whether through ignorance or gross negligence.

Degradation And What It Means To The Supply Chain

The coming years will show a slowing growth rate in the global spending of medicines, particularly when it comes to branded products. Overall, however, total global medicines spend is expected to top $1 trillion by 2015, according to analysis from the IMS Institute for Healthcare Informatics. The compound annual growth of medicines spend is predicted to be between 3–6%, compared with the average 6.2% annual growth that has been witnessed during the past five years.  

The findings stem from the IMS Institute's new study, The Global Use of Medicines: Outlook Through 2015.  

In particular, IMS paints a gloomy picture for branded medicines in the near future. IMS forecasts the spending for branded products to be nearly the same in 2015 as in 2010. However, the market share for such medicines, which fell from 70% in 2005 to 64% in 2010, is expected to decline further to 53% by 2015. The reason? Although there will be increased growth in brand spending (approximately 7–8%, 3–4% of which will come from price growth), this will be more than offset by other dynamics, including patent expiries and changes in national healthcare policies, which will have long-term effects on the spending and usage of medicines across many countries. Due to the market entry of generic products, the loss of earnings for branded sales between 2011 and 2015 is expected to reach $120 billion. 

"Patents are expected to expire in one or more of the developed markets for 11 of the top 20, or 6 of the top 10 current, leading medicines, including Lipitor, Plavix, Advair Diskus, Nexium and Seroquel," explained the report. 

Meanwhile in the emerging markets the growth for branded products is expected to be robust. These markets are expected to nearly double their spending on medicines to reach $285–315 billion, compared with $151 billion in 2010. Approximately 20% of this total increase in spending will come from branded products, but the majority of medicines spend will still be for generic products. IMS estimates that 80 cents of every dollar spent on medicines in the emerging markets in 2015 will be for generic drugs.  

Expenditure on generic medicines is expected to reach $400–430 billion by 2015, compared with $234 billion in 2010 and $124 billion in 2005. A large portion of this growth will be attributable to increased generic competition, as well as incentives from many markets for greater generic usage. In Spain and Italy, for example, generic and off-patent products have been subjected to substantial price reductions to encourage usage. For payers in the developed markets as a whole, the increased use of generic products will translate into net savings of approximately $98 billion in the lead up to 2015. 

The US is expected to see the largest expansion in spending on generic medicines, which will largely come from new generics as US pharmacists already dispense generic products in most instances. In Europe, France, Germany and the UK will also experience significant increases in generics market spend. Both France and Germany are expected to see their share of the generic market expand to reach 21–22%, while the UK will could see its market share reach up to 28%. Out of all the developed markets, South Korea is expected to continue to spend the most on generic drugs. In 2010, the country had a 31.7% share of the generics market. This total is expected to reach 34–35% by 2015.  

Interestingly, although the use of generic drugs is on the rise, the same cannot be said for their biologic counterparts: biosimilars. Even though such products are evolving rapidly, IMS Health expects that only about 1% of total global expenditure on biologics in 2015 will be attributable to biosimilars.  

Speaking about the global spending dynamics as a whole, Murray AItken, executive director at the IMS Institute for Healthcare Informatics, explained in a statement, "Past patterns of spending offer few clues about the level of expected growth through 2015. There are unprecedented dynamics at play, which are driving rapid shifts in the mix of spending by patients and payers between branded products and generics, and across both developed and pharmerging markets." 

The EMA has recently been accused of putting companies' commercial interests ahead of public safety. In response, the EMA has emphasised its recent initiatives to improve data access and transparancy. 

The FDA has added a searchable database of inspection data to its website listing the names and addresses of facilities that the agency inspected in 2009 and 2010. Users can find inspection dates, the type of products produced and the agency's final classification. 

AstraZeneca has settled a sexdiscrimination lawsuit by paying $250000 to 124 female sale specialists who worked at the company's Philadelphia Business Center (PA, US). The lawsuit alleged that the company had discriminated against the women by paying them on average $1700 less than their male counterparts.  

The pharma industry has been called to action by a new report that highlights problems of patient noncompliance. The report estimates that non-adherence to prescribed medicine courses is responsible for an incremental 194500 deaths per year in the EU, resulting in costs close to 125 billion Euros. 

News

The coming years will show a slowing growth rate in the global spending of medicines, particularly when it comes to branded products.

(JANIS CHRISTIE/GETTY IMAGES)The production of lyophilised medicinal products raises many challenges, including identifying critical temperatures, ensuring that the product is processed accordingly, optimising cycles to reduce run times and manufacturing costs, making sure the right containers are used and fit for purpose, and ensuring product uniformity, activity and stability. 

In the past few years, theories and practices in lyophilisation technology have largely remained the same except for small incremental changes, which means that the process as a whole tends to evolve slowly over time. Extensive research is still being conducted to produce a reliable and easy-to-implement endpoint identification method, negating the need for pressure rise tests or temperature probe monitoring. However, several processes and products have recently come on to the market that may benefit the pharma industry. 

One recent innovation is Praxair's Control Lyo Nucleation technology, which allows the freezing point of solutions in freeze dryers to be precisely controlled. Generally, solutions are cooled to below their critical temperature before primary drying is commenced, but the freezing point of different vials can be somewhat random resulting in a non-uniform ice structure, which introduces variability in the drying rate. Praxair's solution could increase control of the process to decrease moisture variability within the product, leading to narrower moisture ranges and potentially reducing the secondary drying time required to achieve acceptable product quality. 

Other developments have come onto the market in terms of packaging; Lyoseal technology (Biocorp) enables vials to be stoppered and crimped within the freeze dryer, potentially saving capping time and helping to ensure container seal integrity. Improvements in glass design, geometry and surface coatings have also helped to reduce vial breakage and cycle times; for example, Easy Lyo (SGD) vials are 30% lighter than traditional vials, and therefore feature improved heat transfer to reduce cycle times. Top Lyo (Adelphi) vials have an ultra-thin hydrophobic transparent layer (40-100 nm) on the internal surface of the vial that helps prevent the collapse of the lyophilisation cake and can almost completely reduce the residual volume. Enhanced vial geometry also provides improved thermal transfer and a dramatic reduction in vial breakage during lyophilisation. There are also products coming onto the market that enable remote temperature probe monitoring. 

These products are relatively new and have yet to be widely used, but all offer potential advantages to the pharma industry in terms of product quality and cost.  

Lyophilisation or freeze-drying is widely used in the pharmaceutical industry for a variety of reasons.

Pharmaceutical Technology Europe-07-01-2011

Overcoming Common Lyophilization Scale-Up Issues

Controlling Nucleation

The Decontamination Challenge

Swiss Pharma Strength

Degradation And What It Means To The Supply Chain

News

Innovation And R&D In Freeze-Drying

Swiss, Please!

Achieving Lean Processing With Single-Use Systems