Advancing Spray-Dried Dispersion Formulation Development

Published on: 
Pharmaceutical Technology, Pharmaceutical Technology-04-01-2021, Volume 2021 Supplement, Issue 2
Pages: s6–s10

In-vitro and in-silico tools can help predict in-vivo outcomes for low-solubility drugs formulated as spray-dried dispersions.

The pharmaceutical industry continues to face challenges developing oral drug products from the large number of low-solubility drug candidates that fall short of in-vivo exposure targets due to poor absorption. Overcoming this issue requires use of a bioavailability-enabling technology that enhances solubility and/or dissolution rate. Spray-dried dispersions (SDDs) are widely regarded as the technology of choice for improving bioavailability, driven mainly by the technology’s applicability to compounds spanning a diverse physicochemical space and its scalable manufacturing process, offering the flexibility and control needed for an optimized drug product (1–2).

SDDs consist of amorphous drug molecularly dispersed within an excipient matrix—typically, a polymer—and are targeted to provide improved aqueous solubility and thermodynamic driving force for absorption over lower-energy crystalline drug forms. Development of SDD formulations, given their metastable form, is inherently more complex than development of crystalline drug formulations. Success hinges on applying an integrated approach where bioperformance, stability, and manufacturability are considered throughout the development cycle, leading to the simplest, most cost-effective strategy to an optimized SDD formulation.

Drug developers may leverage in-vitro and In-silico tools to obtain ideal in-vivo outcomes for low-solubility drugs formulated as SDDs. Specifically, In-silico preformulation tools and physiologically based pharmacokinetic (PBPK) modeling strategies may help increase understanding of bioperformance mechanisms and make early in-vivo exposure predictions; and in-vitro test selection and design based on drug physicochemical properties, target dose, and species can help advance development.

Belinostat, a poorly soluble drug, offers an example of how drug developers have used in-vitro and In-silico tools to optimize in-vivo performance (3). The chemical structure and physicochemical properties of belinostat are highlighted in Figure 1 and Table I, respectively. As the small-molecule pipeline contains more solubility-challenged molecules, SDD formulation may become an increasingly important part of the drug development toolkit.

In-silico preformulation tools for compound classification

A preliminary assessment of some of the key absorption hurdles a drug candidate might face in vivo is crucial at the outset of a SDD formulation campaign. The goal is to establish a hypothesis about the rate-determining step to in-vivo absorption, so an initial formulation strategy can be devised regarding selection of the SDD matrix polymer and drug loading.

A preformulation assessment typically starts by predicting and/or measuring the drug’s physicochemical properties and using this information to perform some simple dimensionless-number calculations as part of the Biopharmaceutical Classification System (BCS) and Fraction Absorbed Classification System (FaCS) (4–5). These industry-standard methods are designed to identify potential barriers to absorption based on compound physicochemical properties and projected dose in vivo. Barriers to absorption generally include drug dissolution rate, solubility, and/or permeability, all of which play a direct role in drug absorption. In the case of belinostat, a fasted beagle dog study was planned at a 50-mg dose to get an initial read on the relative performance of a belinostat SDD formulations compared to that of the crystalline drug form.

For this test plan, the dissolution (Dn), permeation (Pn), and dose numbers (Do) can be calculated using measured aqueous solubility data and the physicochemical properties for crystalline drug. For crystalline belinostat dosed to fasted beagle dogs at a 50-mg dose, the FaCS classification suggests crystalline belinostat will demonstrate solubility-limited absorption. The calculation methods, details of each limiting case, and specific values for belinostat are shown in Table II.

By assessing the rate-limiting case for absorption at the outset of a drug development program, efforts can be focused on the most-promising technology (e.g., SDD) while weighing the associated benefits and risks. In the case of belinostat, it was clear that if absorption were to be improved, the best path forward would likely be via SDD formulation, because both aqueous solubility and dissolution rate would increase compared to crystalline drug, likely leading to improved absorption and bioavailability.

In-vitro tools for formulation design and bioperformance evaluation

After using In-silico problem statement identification tools, developers may then select and design in-vitro tests based on three main criteria: the physicochemical properties of the compound, the target dose and species, and the key performance attributes of the formulation based on the (hypothesized) rate-limiting step to absorption and target pharmacokinetic profile.

For belinostat, the key tests employed during SDD development were, first, amorphous solubility/polymer screening and, second, a gastric-to-intestinal transfer test to determine dissolution performance. Fiber-optic ultraviolet (UV) probes are used for these tests, which are described in Table III. Data from the tests are used as inputs into a pharmacokinetic model for in-vivo predictions.


Amorphous solubility/polymer screening. The test for amorphous solubility/polymer screening is often the first and most important in-vitro assessment before formulation screening. Amorphous solubility is measured via solvent-shift UV assay with fiber-optic UV probe detection, where drug is titrated from a stock solution in organic solvent into a dissolution medium of interest (with and without predissolved polymer). As stock solution is titrated, wavelengths are monitored beyond the UV cutoff of the drug in an attempt to observe any light scattering that occurs once liquid-liquid phase separation is reached, the key indicator of the amorphous solubility.

Key outputs of this test are shown in Table III and described as follows:

  • Drug amorphous solubility: Provides an initial assessment of the solubility benefit of the amorphous form relative to crystalline drug, which can be fed back into the FaCS calculation to reassess, if necessary, the rate-limiting parameter for absorption of the amorphous drug form.
  • Polymer sustainment: Measures the ability of each polymer to sustain supersaturated drug concentrations (i.e., sustainment), a critical metric for success for most SDD formulations.
  • Drug/polymer interaction: Identifies unique drug behavior in the presence of each polymer (e.g., polymers may suppress the drug amorphous solubility).

For belinostat, this test showed the amorphous solubility was substantially higher than the crystalline aqueous solubility (Table IV). Sustainment of supersaturation was excellent for the three polymers that were evaluated: polyvinylpyrrolidone (PVP K30), PVP vinyl acetate (PVP VA64), and the M grade of hydroxypropyl methylcellulose acetate succinate (HPMCAS-M). Interestingly, the amorphous solubility of belinostat was significantly altered by the presence of polymer and was specific to each polymer type. This result suggests that polymer selection for formulation screening would hinge more on the attenuation effect of the amorphous solubility than on sustainment of supersaturation. It also suggests that each formulation has a different ceiling with respect to the overall solubility enhancement relative to crystalline drug.

Lastly, recalculating the FaCS classification for amorphous belinostat suggests that belinostat SDDs will be dissolution-limited rather than solubility-limited, driven by the formulations’ substantial solubility enhancement over crystalline belinostat. As such, maximizing the rate and extent of SDD dissolution should be a key focus area.

Fiber-optic UV probe dissolution. Dissolution testing using fiber-optic UV probes is a quintessential part of the in-vitro bioperformance toolkit for many drug developers and manufacturers. Fiber-optic probes afford the opportunity to perform real-time data collection and analysis with high time resolution and minimal effort compared with conventional manual sampling methods. They also provide the opportunity to perform orthogonal characterization concurrent with the experiment to establish a mechanistic understanding of formulation performance with respect to dissolution, precipitation, and drug speciation.

Given the results of the amorphous solubility/polymer screening test, prototype SDD formulations were manufactured at a 25% (w/w) belinostat drug loading with PVP VA64, PVP K30, and HPMCAS-M. These formulations were then tested in a gastric-to-intestinal transfer dissolution test. Experimental conditions were chosen based upon the amorphous solubility results and the nominal dose/volume for a fasted beagle dog to optimize biorelevant conditions. Test conditions, method descriptions, and results are shown in Figure 2.

The dissolution data aligned well with the amorphous solubility results for the SDDs in simulated gastric fluid (SGF) (nonsink dose) with the exception of the HPMCAS-M SDD. HPMCAS-M is an enteric polymer with low solubility at pH values below 5.5, resulting in limited dissolution of belinostat from the SDD particle in SGF. In simulated intestinal fluid (SIF) (sink dose for all SDDs), the results suggested the following rank by performance: PVP K30 > HPMCAS-M > PVP VA64. The PVP K30 SDD was clearly superior in SGF, providing the highest dissolution rate and dissolution extent of all SDDs.

Pharmacokinetic modeling for hypothesis testing and in-vivo prediction

The final step before in-vivo evaluation is to build a pharmacokinetic model incorporating key in-vitro data for prediction of in-vivo performance. The goal is to continue the hypothesis-driven formulation strategy by setting expectations in vivo that are aligned with the formulator’s understanding of drug physicochemical properties, in-vivo study design, and how each formulation performs in vitro with respect to dissolution, precipitation, and drug speciation.

For belinostat, this includes incorporating physicochemical properties, amorphous solubility data with unique solubility inputs for each SDD, as well as dissolution kinetics for each SDD in both the stomach (ca. pH 2) and the intestine (ca. pH 6.5). Pharmacokinetic parameters were established using intravenous data generated in beagle dogs, and the resulting simulations were compared to the observed in-vivo data results (Figure 3).

Results suggest that the simulation using amorphous solubility and dissolution data did an excellent job predicting the in-vivo outcome. Additional model parameters for sensitivity analysis (not shown) helped elucidate the key metric for in-vivo success for these formulations: dissolution rate and extent of dissolution achieved in the stomach before gastric emptying into the intestine for absorption.


SDD technology is a unique and broadly applicable platform for improving the oral bioavailability of poorly soluble drugs. However, successful SDD development requires a deep scientific understanding of amorphous systems and their behaviors in vivo. Leveraging In-silico and in-vitro tools when developing SDD formulations saves time and resources during development by improving understanding of the key barriers to absorption, as does possessing the tools to accurately evaluate these types of formulations in vitro.

The belinostat SDD case study demonstrated the use of these tools and concepts, ultimately leading to an optimized outcome and successful in-vivo testing. As low-solubility and low-bioavailability molecules grow more prevalent in small-molecule drug development, having access to best-in-class SDD manufacturing capabilities may become more important for pharma and biotech innovators. Working with external partners may help provide access to these capabilities, particularly for smaller or emerging firms that often lack sophisticated manufacturing capabilities in-house.


1. D.E. Dobry, et al., J Pharm Innov 4(3) 133–142 (2009).
2. A. Singh and G. Van den Mooter, Adv Drug Deliv 100 27–50 (2016).
3. A. Stewart, et al., J Pharm Sci 108(1) 326–336 (2019).
4. K. Sugano and K. Terada, J Pharm Sci 104(9) 2777–88 (2015).
5. G.L. Amidon, et al., Pharm Res 12(3) 413–420 (1995).
6. E.R. Grignard, et al., Eur J Pharm Sci 99 193–201 (2017).
7. M. Arndt et al, Eur J Pharm Biophar 84(3) 633–641 (2013).
8. P.K. Gupta and J.R. Robinson, Int J Phar 43(1) 45–52 (1988).

About the author

Aaron Stewart is associate principal scientist at Lonza Pharma and Biotech, Bend, OR.

Article Details

Pharmaceutical Technology
Supplement: Solid Dosage Drug Development and Manufacturing
April 2021
Pages s6–s10


When referring to this article, please cite it as A. Stewart, “Advancing Spray-Dried Dispersion Formulation Development,” Pharmaceutical Technology, Solid Dosage Drug Development and Manufacturing Supplement (April 2021).