Multispecific antibodies are of interest to drug developers because they provide an avenue for achieving more effective or safer treatments for a wider range of diseases. Those attributes result from their ability to simultaneously target or engage multiple protein targets. Unfortunately, a consequence of this enhanced capability is greater structural complexity, which is often accompanied by greater numbers of charge and structural variants and potentially a wider range of post-translational modifications (PTMs). Drug developers need to obtain deep understanding of these highly complex biomolecules as early as possible in the drug development process to avoid investing time and cost into nonviable candidates. Analytical techniques that provide better information, earlier, are needed to facilitate multispecific drug development.

Greater complexity than traditional monoclonal antibodies

Multispecifics are made up of similar domain structures as monoclonal antibodies (mAbs). They are more complex, however, and that complexity is increasing as antibody developers seek to tailor binding and half-life to specific biological requirements while also addressing steric considerations for multiple target engagement, according to Donmienne Leung, head of protein engineering at Absolute Antibody.

The challenge, says Susan Darling, senior director of capillary electrophoresis and biopharma product management and marketing at SCIEX, is that there are many more variants associated with these complex structures.

“Standard mAbs have identical heavy and light chains, but there are charge and sequence variants and many different post-translational modifications that afford many different isoforms. For multispecifics, the number of possible structural variants is greater and depends on how many different components are being combined together. Each one of those structure variants has its own range of isoforms. That makes the analysis of multispecifics exponentially more complicated,” she explains.

If multispecifics are produced with stochastic expression systems, inappropriate association of the different chains may occur. That makes even size assays for identifying intact mAbs inapplicable, because the different structural combinations may have the same size, but only the correctly assembled molecule will exhibit the desired activity. All of the rest are considered impurities. In addition, the greater structural complexity of multispecifics may result in a greater tendency to misfold and aggregate, comments Leung.

Furthermore, Darling notes that even if a strategy, such as the “knob-in-hole” approach, is used to afford multispecifics with the correct structures, the bioengineering process typically introduces more attributes to these proteins, such as different modifications, that make these biologics more complex not only structurally but from an affinity perspective.

The increased number of undesired side products may potentially make purification of the requisite therapeutic by traditional chromatography techniques more difficult, adds Leung. “Multiple chromatography steps and mass spectrometry (MS) become necessary for full characterization of the multispecific. The evaluation of multiple target binding will also be less straightforward when the geometry of the multispecifics and accessibility of each binding domain can be highly dependent on assay formats,” she states.

Similar characterization needs, plus much more

That greater complexity means that for multispecifics, all of the characterization and other assays required for monospecifics are required, plus many more. Specifically, it is crucial to confirm the correct folding and intramolecular pairing of various domains. As an example, Leung highlights the need to confirm the correct pairing of heavy chain to light chain for each specific antibody arm to retain affinity to the required target of interest.

“We can no longer assume that two heavy and two light chains will come together in a symmetrical molecule,” Darling agrees. “Many different combinations with minimal mass differences can be generated depending on whether the platform involves stochastic expression or not,” she says.

In addition, while the mispairing of both the heavy and light chains is often of critical importance for the potency and safety of mAb-based bispecific formats, it may not be a factor for other formats, observes James Graham, director of protein and process analytics within the Bio R&D group at Lonza. “Even though similar methods can be used, the range of multispecific formats means that ‘new’ attributes are specific to the individual format for the protein rather than broadly relevant for all multispecifics,” he notes.

Multispecifics built using Fc and antibody fragments, Leung continues, can be purified and analyzed similarly to traditional antibodies and proteins using affinity chromatography (Protein A, nickel, etc.). “The purity and homogeneity of multispecifics can be achieved and evaluated by a combination of chromatography (e.g., hydrophobic interaction, ion exchange, and size exclusion) and MS similar to traditional biologics, while PTMs on recombinant proteins and multispecifics are typically characterized by mass spectrometry,” she says.

Assumptions made for immunoglobulin (IgG) monospecifics don’t apply to multispecifics, Darling adds. “The assumption for monospecific IgGs that there will be Fc and target binding affinities is also no longer applicable. Two or three different binding affinities can be competitive against different targets,” she contends. In addition, she notes that there are often modifications in multispecifics that are not observed for mAbs because of the way the cell lines used to produce these biomolecules are engineered. There can be additional PTMs as well, and in particular more variability in disulfide bonds.

It is important to remember, though, Graham underscores, that mAbs themselves are already multispecifics, so there already is a good baseline in terms of knowing what needs to be monitored. “In addition to established attributes we monitor during mAb development (e.g., safety, purity, potency, and the range of product variants such as glycosylation), it is the specific modifications that have been made from the established mAb framework that need special attention. These may vary substantially depending on the protein architecture,” he concludes.

All of these variations, Darling asserts, can impact binding affinities and thereby make many other assumptions about monospecific IgGs also nonrelevant for multispecifics. “There can be different cross-reactivities, different catabolite forms, and different isoforms generated during the biotransformation process that can all have modified binding capacities. Simple ligand binding assays are no longer sufficient,” she says.

Leung also stresses that in addition to all of these issues, it is important to remember that multispecifics must be monomeric, soluble, and stable in nature to enable clinical development and downstream commercialization.

From a characterization standpoint, the big challenge for multispecifics is the increased possibility for greater higher-order-structure variability, according to Darling. “The molecular asymmetry and potential for multiple product-related impurities based on the combinations of chains being expressed is the source of this variability,” Graham notes.

The fact that protein structures, including multispecifics, when in solution are dynamic in nature with flexible structural isomers and potentially aggregated molecules further complicates bioanalysis, according to Leung. “Temperature can also influence the overall stability of the correctly folded molecule and the respective domains. Moreover, the surface interactions between molecules and between domains may have significant impact on self-association,” she comments.

Where there are significant molecular weight differences between potential product variants, Graham adds that the assessment of aggregation can become challenging because a high-molecular-weight species could represent a protein aggregate or a mispairing variant.

This variability can also create hurdles during process optimization and scale up once a multispecific product is defined and an investigational new drug application (IND) has been filed. “With multispecifics, there simply are more chances because of the higher variability that any changes to the process will lead to the formation of the wrong structures and/or isoforms. That means the risk is greater. It also means that many more samples must be evaluated in a way that provides detailed information very quickly,” Darling says.

It is generally necessary, observes Darling, to use a combination of intact mass measurements and characterization with reductive techniques such as digestion prior to subunit analysis or peptide-level analysis to identify disulfide bonds.

A key trend in the biopharma industry affecting all drug development is the desire to compress development timelines down to just a few years. “Companies are looking to get development times down to 1000 days; they want to develop everything at pandemic speed, even when they have diverse portfolios that include highly complex next-generation products such as multispecifics, gene and cell therapies, and RNA-based treatments, all of which require new and different analytical capabilities,” Darling asserts.

The result is a unique situation in which a usually risk-averse industry, because it is rapidly moving to more complicated molecules, needs access to newer, perhaps initially slightly more experimental technologies. “The industry is really driving to be creative, not just in terms of analytical solutions, but in how they manage data and pull it together to knock the inefficiencies out of every step,” Darling concludes. “Our customers are challenging us to develop new analytical techniques that provide more information more quickly, and when we bring them new solutions, they are adopting them at a much faster rate than could ever be imagined even a decade ago,” she says.

The reason for this transformation within the industry is a new focus on the developability of biologics. “Developability is increasingly critical for downstream commercialization,” Leung states. Darling agrees. She says that the strategy of failing fast and early has been increasingly adopted at an accelerating rate over the past few years, with companies looking for technologies that enable more detailed characterization and stability assessments early on.

“Simply selecting the highest-yielding cell line without considering the product quality is no longer the typical approach. Developers want to find the right cell line and clone that produces a high yield of the desired product—mAb or multispecific—with the right structure and modifications from the outset to avoid costly late-stage failures,” Darling explains.

For instance, Leung points to the use of various 

 and pre-clinical screening techniques for the evaluation of non-specific binding, self-association, and chemical stability as means for identifying problematic molecules early on. She also notes that while sequence analysis and 

 assays have been recognized for the pre-clinical prediction of immunogenicity risks associated with traditional mAbs, these techniques have not been correlated for multispecifics with confidence.

Developers are also looking for high-throughput, highly informative, easy-to-use analytical solutions that support this strategy. For multispecifics, one of the challenges is the inability to apply platform analytical strategies because of the variety of formats. Product-specific methods become critical, and these methods are required early in development, according to Graham. “As well as ensuring that method performance is sufficient to monitor the attribute in question, throughput and turnaround times must be compatible with screening stages during cell line and process development,” he says.

Orthogonal approach to analysis essential

Comprehensive characterization of multispecifics, because these biomolecules are so complex, generally requires the use of several orthogonal methods. In addition to traditional antibody assays, many other methods are being explored.

“There are many different attributes of multispecifics that need to be determined, and because this type of biologic is relatively new, there is still work to be done to determine which methods are best,” Darling observes. There is a need, she adds, for iteration and customization of technologies to determine which will be most impactful and robust. As a result, multispecific developers are leveraging orthogonality, using multiple assays to confirm results and build more confidence in their data.

For instance, in addition to leveraging established techniques such as ultra-high performance liquid chromatography (UHPLC), capillary electrophoresis (CE), surface plasmon resonance (SPR), MS, and automated cell-based analysis platforms, techniques that can easily identify peaks within a profile are crucial, according to Graham. Native MS is one such technology that can be used to generate peak identity information in parallel to the primary analysis method, rather than having to perform subsequent follow-on testing. “Native MS is particularly interesting due to the information density of the technique and the fact that non-covalent variants or impurities may be present for some multispecific formats that can be challenging to characterize using other methods,” he remarks.

In general, adds Leung, a combination of high-resolution LC and MS techniques are necessary to fully characterize multispecifics. Thermal stability analyses such as differential scanning calorimetry (DSC) and differential scanning fluorimetry (DSF) allow developers to select for better-behaved molecules. CE and other electrophoretic techniques such as isoelectric focusing (IEF) and capillary IEF (cIEF) have improved resolution of traditional sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS-PAGE) methods in elucidating the correct pairing of polypeptide chains in multispecifics.

Intact mass analysis using Orbitrap-based LC-MS can resolve all theoretically expected species in a complex mixture, while using electrospray ionization time-of-flight (ESI-TOF) MS on quadrupole instruments enables quantification of various species with improved sensitivity and robustness.

While target binding can be confirmed using simple enzyme linked immunosorbent assay (ELISA) methods, biochemical characterization of multispecifics requires detailed kinetic analysis to compare the integrity of the final product. Association and dissociation phases of molecular interactions can be measured by established techniques including SPR, biolayer interferometry (BLI), and isothermal titration calorimetry (ITC).

Ultimately, though, Leung concludes that cell-based assays are necessary to confirm target engagement and the desired functional activity of the multispecific.

With so many options for analyses to perform, it can be quite challenging to determine which methods should be used for a given multispecific. Lonza has found that having a template library of different analytical methods based on the chemistry of the therapeutic protein provides a starting point for method development. “When combined with a design-of-experiment approach, development cycle for the deployment of a new method can be greatly streamlined and development times reduced from weeks to days or less!” Graham avers.

New tools for accelerating multispecific development

With an overall goal of accelerating biopharma development, SCIEX has focused on meeting the needs for easier-to-use MS solutions that provide rapid, detailed results. In 2021, the company introduced the accurate mass ZenoTOF 7600 system, which leverages both Zeno trap with electron activated dissociation (EAD) fragmentation technology.

In traditional TOF instruments, Darling explains, the fragment ions arrive at the pulser region with a spread of velocities, so only a small percentage of the ion population gets accelerated into the flight tube. This duty cycle problem is overcome because the Zeno trap enables all of the ions to arrive at the TOF pulser at the same time independent of their masses. More than 90% of the ions are injected, resulting in significantly improved MS/MS ion sampling for all m/z and greater sensitivity for MS/MS and high-resolution multi-reaction monitoring (MRM) acquisition scan modes and greater ion fragment coverage.

EAD, meanwhile, provides for generation of electrons with tunable velocities and allows for different fragmentation mechanisms, including the hot ECD mechanisms ideal for peptide mapping of glycopeptides and disulfide-bonded peptides, according to Darling.

Importantly, EAD preserves valuable side chain information, such as for labile PTMs very common in multispecifics, that enables confirmation of various isomers and affords excellent MS/MS coverage for all charge states in one experiment. “We are finding real interest in this technology because it allows for much easier and more robust characterization of even highly complex molecules. In fact, for the first time it could be possible that electron dissociation could become the go-to-choice for fragmentation,” Darling asserts.

Another advance in MS technology is in the works at SCIEX and is based on the direct coupling of cIEF with MS. Initially developed by IntaBio, which SCIEX acquired in early 2021, the system enables high-resolution separation of charge variants combined with detailed MS data for each variant. “The combination of isoelectric point directly coupled with MS data allows for confident identity assignment during intact analysis in much less time than is required for conventional peptide mapping analyses,” Darling notes. The company expects to launch the system sometime in 2022.

On the CE front, SCIEX has introduced in 2021 a new system that allows for much higher throughput analysis. “The BioPhase 8800 system leverages a new cartridge that allows parallel processing of eight different CE samples (same or different molecules) simultaneously using CE-SDS and/or cIEF with UV or LIF detection, providing all the advantages of CE while delivering consistent, accurate results so that more samples can be analyzed in less time,” Darling explains.

Importantly, methods developed for SCIEX’s widely used PA 800 system can be transferred to the BioPhase 8800, avoiding any need to do bridging studies as projects move to late-stage development and commercialization. “That can save weeks to months of time,” Darling says. “In addition,” she emphasizes, “companies can rapidly perform design-of-experiment studies to quickly optimize both assays and manufacturing processes.”

More complex molecules and the need to perform more orthogonal analyses means that more samples must be prepared and much larger data sets are generated that must be analyzed. Automation of both of these aspects of multispecific analysis is becoming another crucial strategy for speeding up the development process. “Biopharma companies are looking for any opportunities to remove unnecessary manual processing, whether with respect to sample preparation or data processing,” comments Darling. That includes investing in more specific software products, many of which leverage artificial intelligence and machine learning, to help with data integration.

While standardizing assays for multispecifics is not possible given the unique nature of each of these biologics, automation of sample preparation and data acquisition and analysis can help simplify these solutions, Darling insists. High-throughput data analysis platforms, agrees Graham, are critical to the deployment of newer analytical methods for multispecifics into process development, because otherwise the data analysis time quickly dominates the overall time to result.

The challenges associated with multispecific analysis, while real, are not so great that the bioanalytical experts with experience in biologics development cannot manage them. “Multispecific analysis is definitely an interesting field, but it should not be considered a major risk,” Graham asserts. “Rather, analytical development for these complex biomolecules should be approached with a structured but flexible workflow combined with a good understanding of each molecule’s chemistry,” he concludes. Having multiple answers on hand for multiple multispecifics works!

Cynthia A. Challener, PhD, is a contributing editor to 

Articles

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The multispecific analysis of biologics is a complex task that requires appropriate strategies.

Multispecific Analyses of Biologics Pose Multiple Challenges

The complexity of biologic drug substances requires specialized analytics and the training to do the analyses. It is not enough to know how to run the assays, but also how to interpret the data to give meaningful clinical value to the analyses. To gain insight into methods with which biologics drug substance testing results must be analyzed and interpreted as well better understand the challenges inherit in dealing with complex biological molecules, 

 spoke with Khanh Ngo Courtney, senior director of Biologics at Element, and Mahesh Bhalgat, chief operating officer of Syngene International.

 Is there currently a lack in lab personnel with the specific skill sets to interpret data from biologic drug substance testing? If so, what skills training is in most dire need?

 More and more, we are seeing that the characterization and routine testing of biological therapeutics, particularly of advanced therapeutics such as gene and cell therapies, require advanced analytical techniques combined with a thorough understanding of biology, which requires specialized lab personnel. For example, enzyme-linked immunosorbent assay (ELISA) is becoming a less effective way to quantify host cell protein (HCP) clearance due to emerging data showing that antibodies generated against the HCPs do not provide sufficient host cell proteins coverage. Hence, a more comprehensive analysis of HCPs is required. Liquid chromatography–tandem mass spectrometry (LC–MS/MS) is emerging as a needed analytical method to quantify and characterize HCP clearance. Finding talent who could develop and perform a robust, chemistry, manufacturing, and controls (CMC)-appropriate, quantitative LC–MS/MS method for HCPs is challenging.

Similarly, biological therapeutics require an 

 cellular assay to show potency during characterization and for release and stability testing. The design and development of the appropriate cellular potency methods, including the method for read-out, require personnel who understand the mechanism of action of the therapeutic, and how to exploit the cell biology toolbox to show 

 efficacy of the drug in a robust and CMC-appropriate manner. The appropriate skillset required to perform this type of work is not easy to find in one individual.

 Biological drug substance testing is rapidly evolving, and new platforms and technologies are being used for testing purpose to suit the needs of the assays and drug mechanisms. While many labs and lab personnel are technically sound, there is still a lack of understanding and decision-making on the use of analysis models for biological product characterization and for the mechanism of action (MoA) studies. We find the greatest shortage in laboratory personnel is scientists trained on the statistical designs, analysis, and validation of the qualitative assays.

Additionally, there is a lacuna in getting professionals with biologics analytical training, especially in the structural and functional characterization areas. Apart from the physicochemical area, there is a need to strengthen the knowledge base on analytical ion exchange chromatography and N-glycan analysis for glycosylated biologics.

 What have been some of the major challenges in interpreting and analyzing data generated from drug substance testing of biologic APIs?

Bhalgat (Syngene): Drugs, including APIs and biologics, must be manufactured in compliance with appropriate quality standards. Some of the major opportunitiesassociated with analysis and interpretation of data from testing of biologics include product- and process-related impurity identification and analysis, which is always challenging due to the specialized nature of testing; assay changes during stability studies due to noncovalent interaction-driven oligomer formation; and HCP analysis of in-process samples.

The major challenge lies in interpreting data for its significance when it lacks large data sets generated over a sustained period. Since monitoring and analyzing the trend of the data is important for biologics and other drugs, we apply quality-by-design (QBD) approaches for ensuring data interpretation and comparison needs are met.

 The heterogeneity of the biological molecule impacts how methods are developed, data are generated, and interpreted. Large molecules are tens, if not hundreds, of thousands of small molecules chemically interacting with one another to form tertiary structures, which translate to function. Yet, not all the molecules in a solution of the drug substance are going to be exactly the same—they vary in the amount of post-translational modifications such as glycosylation, phosphorylation, and other chemical modifications as well as endured damages, such as amino acid deamidation, reduction, and oxidation. All of these chemical modifications together impact the structure of the biological molecule, its function, and how it interacts with other molecules in the cell and how it behaves in analytical methodologies.

 What methods or approaches have thus far been successful in generating clinically meaningful data and analyses of that data?

 Meaningful data in the clinic require that the appropriate biomarkers are selected, and the methods for detecting and quantifying said biomarkers are robust and sensitive. The Meso Scale Discovery (MSD) and Quanterix immunological technologies are common methodologies and have been successful in the analysis of clinical samples. LC–MS/MS, if available, remains a powerful tool for the analysis of clinical data for its sensitivity and robustness in detecting and quantifying not only large molecules, but small-molecule biomarkers.

 In clinical research, obtaining meaningful data is built on several factors. Best practices that have been successful in generating clinically meaningful data and have aided the interpretation/analysis of the generated data include drug-specific pharmacokinetic (PK), pharmacodynamic (PD), and immunogenicity assays, rather than generic/off-the-shelf kit assays or methods. Validated methods are also required in assuring assay performance, as per expectations for the set dosage, administration route, and intended clinical interventions. In addition, a careful review of the clinical trial protocol early in assay development, including a two-way dialogue between the clinician and the bioanalytical scientist, helps in setting up fit-for-purpose methods for the relevant trial. Finally, paying special attention to the performance of the method for a particular trial subject population, their age, disease state, ethnicity, etc., helps in generating reliable data.

 Where is there the most unmet need in term of analytical solutions for complex and challenging biologic drug substance testing?

 The bioanalysis of biologics requires the ability to use many different approaches, so there are many unmet needs. For instance, there is a need for high throughput automation and practical biostatistics for complex and challenging biologic drug substance testing. Meanwhile, immunoassays for biologics are labor-intensive and people-dependent. The move to much more automated technology for conducting sensitive and specific immunoassays is a clear opportunity. There is also a need for the availability of assays for biophysical characterization in the presence of various process matrices, host-specific, HCP assay, and non-destructive assay to understand the tertiary structure of drugs at the atomic level (for example, cryo-electron microscopy or single-molecule fluorescence techniques are yet not available for industrial use). Additionally, due tolack of proper guidelines, and there are differences in regulation across different geographies resulting in the development of varying approaches to testing products.

 Highly complex biological drug substances, such as genetic information in the form of viral or nanoparticle encapsulated therapeutics (e.g., lentivirus, adeno-associated virus [AAV], nanoparticles), are extremely difficult analytically due to the heterogeneity in the quality of the drug substance. One example is the analytical challenge of separating and quantifying fill-amounts of viral particles (i.e., empty vs. partial vs. full). When AAV or lentiviral APIs are produced, the drug substance solution will comprise partially of viral particles containing the correct number of copies of genetic information, particles with too much material, particles with too few, and particles containing no material at all. Having the analytical capability and technology to obtain resolution between these different molecular compositions of the drug substance is still an unmet need. Current methods all have their own pitfalls. Analytical ultracentrifugation is expensive, not robust, and requires a significant amount of sample. Transmission electron microscopy is time-consuming and lacks quantitative power. High-performance liquid chromatography has poor resolution. Finding the right analytical solution for the intended purpose is unmet need for many quality-defining methods for advanced therapeutic molecules at the moment.

Feliza Mirasol is the science editor for 

Personnel need to be trained in various analytical skill sets for biologic drug substance testing.

Analytical Skills Are Needed in Biologics Testing

Toxicology studies are employed in drug development to evaluate the safety and viability of potential drug candidates, and the data from such studies are used to support regulatory submissions. As it is widely known that toxicity is a contributing factor to drug candidate attrition and with demand for faster and cheaper drug development increasing, researchers are looking at ways to perform toxicology studies as efficiently as possible.

To learn more about toxicology studies, including how accelerated timelines impact these studies, the expectations and requirements of regulatory bodies, issues surrounding animal models, and possible alternative assays, 

 spoke with Steven Bulera, PhD, DABT, corporate vice-president, global head of Toxicology, Charles River Laboratories.

 Could you elaborate on the importance of toxicology studies?

 When developing a new therapeutic, the new therapy must demonstrate two simple criteria. First, the therapy must be efficacious: it must treat the disease or improve the quality of life of the patient. Second, the therapy must be safe and not cause additional and/or unacceptable harm to the patient. Toxicology studies are designed and conducted to identify and characterize any potential adverse events or toxicities prior to the new drug being administered to patients or volunteers participating in clinical trials (1). To accomplish this task, a variety of nonclinical toxicology studies are performed in non-human 

 models. Additionally, these studies are required for regulatory submissions around the world and support ‘first-in-human’ clinical trials and clinical trials needed to bring the drug to the market and to patients in need.

In addition to characterizing potential adverse events, toxicology is important in that the studies conducted help identify and remove potentially ‘bad’ drugs from development, which protects patients from potentially harmful drugs and removes drugs from development before large financial investments are made in drugs that have limited or no potential to be a successful new therapy.

 What type of toxicology studies are performed in drug development?

 The types of studies run include general toxicology (various durations), genetic toxicology, safety pharmacology, reproductive toxicology, and carcinogenicity bioassays. Additionally, other specialty studies may be run to identify abuse/seizure liabilities, musculoskeletal toxicities, neuro-toxicities, ocular toxicities, and/or phototoxicities that could potentially be caused by the new therapeutic. The 

 studies are run in a variety of cell types, and the 

 studies are typically run in two species (a rodent and nonrodent species). In general, regardless of the new drug modality (small molecule, monoclonal antibody, gene therapy, oligonucleotide, protein, etc.), the study designs and endpoints are similar.

Where differences are seen are with the specific biomarkers that are included in the study and are based on the specific type of molecule and the target of the new drug. It is important to mention and acknowledge that while many of the toxicology studies use animals, the studies are designed with the 3Rs (reduce, refine, and replace) in mind and that the animals are treated humanely with the highest standards of animal welfare in mind.

 How might accelerated development timelines impact toxicology studies?

 When there is an unmet medical need, the question that is always on a researcher’s mind, is ‘how fast can we get this drug to the patients that need it?’ A common trend in drug development is ‘how do we go faster?’ To support accelerated programs, toxicology has developed faster ways to generate, analyze, and interpret data, as well as faster ways to create the reports needed for regulatory submission. Additionally, some of the best practices that can be called upon involve strong partnerships between clients and contract research organizations (CROs) so that both parties are working together to remove white space from study initiation and reporting timelines. Milestones can then be reached more rapidly.

Also, companies have developed paradigms that require decisions to be made at risk or in parallel with the reporting process to move to the next steps faster. Often, companies wait for final reports to make decisions. To accelerate the toxicology program, companies are encouraged to make decisions on data, and then start the next study/phase before the previous study report is finalized. This [method] can remove weeks if not months from a toxicology program.

 What are the regulatory expectations and requirements for toxicology studies in drug development, both for a regular timescale and an accelerated one?

 The vast majority, if not all, toxicology studies used for regulatory submissions are run under good laboratory practice (GLP) regulations. These are a series of regulations required by countries that dictate how studies must be conducted to ensure that the studies were conducted with the highest scientific quality. Additionally, these regulations have documentation expectations so that regulatory agencies reviewing the toxicology study package can know how the studies were conducted and that they can accurately recreate the study from what was documented.

Regardless of whether the new drug was conducted under a standard or accelerated timeline, countries have the expectation that the studies were conducted under the auspices of the GLPs. Where there is some potential flexibility for the toxicology program, is what individual studies are needed and the duration of those studies that are required to move the drug to the next development milestone. There are examples for rare and orphan disease therapies, where regulatory agencies have been open to alternative toxicology study designs and customized toxicology packages so that these drugs can get to patients that need them faster.

 Could you run through some of the issues surrounding animal models for toxicology studies and what possible solutions there may be in the pipeline or already being used that could benefit industry for wider adoption?

 Some of the common reasons cited as to why whole animal toxicology models are not appropriate to use in drug development are that animal models do not reliably predict human outcomes, drugs that appear to work well in animal models fail to work when given to humans, and having to use animal models and run animal studies delays the drug development process. Numerous articles exploring the limitations of these models have been published (2–4).

Alternatives to the use of animal models are also continually being discussed and developed. We have seen advances made using 

 models (1D, 2D, 3D cell cultures, tissue slices, organs-on-a chip). As an example, for many years chemical irritancy was tested by administering compounds to the eyes of rabbits (Draize eye irritation assay). However, that assay has been replaced by the 

 Bovine Corneal Opacity and Permeability (BCOP) assay that only uses animal corneas that normally would have been discarded.

Also, researchers continue to look at alternative models for testing the toxicity of compounds. Khabib 

 outline the advantages and disadvantages of using alternative models such as brine shrimp, zebrafish, daphnia, copepods, molluscs, and so on (4). These 

, and alternative animal models are useful for identifying if a compound is toxic, can be used as screens to rank order compounds from more to less toxic, and can be used to determine if a compound impacts a specific cell type or a specific cellular pathway. However, they currently do not capture the complex interactions with organ pathways (i.e., communication pathways between cells and organ systems) that are linked together in a whole animal model.

While the predictiveness of animal toxicology models may not be as predictive of human outcomes as researchers would like, history has shown that the testing performed using these whole animal toxicology models has and continues to protect humans/patients from harmful drugs. In addition, the more that is learned about cellular and biochemical mechanisms, and how organ systems operate and communicate, the predictiveness of our models will also improve. Also, as researchers continue to learn about how to better care for and manage research animals, the reproducibility of results will also improve. Even as the predictability and reproducibility of whole animal models improves, researchers will continue to look for assays/methods to replace animal toxicology models in an effort to reduce animal usage (3Rs), bring drugs to ‘in need’ patients faster, and to appreciate the value that these alternate methods bring to drug development.

 Might the use of computer simulations (or other disruptive technology) become the industry standard for toxicology studies in the near future?

 As new data are obtained about cellular pathways, organ systems, and cellular communication networks, and are combined with information about the new drug (structure data, similarity to previously tested drugs, absorption, distribution, metabolism, and excretion data, 

 data, etc.), it is conceivable to envision a time when it will be possible to employ artificial intelligence and machine learning algorithms to characterize new drugs completely 

. There are numerous examples in the literature, where 

 methods have been used as accepted replacement/substitutes for whole animal models or for examining specific biomarkers. However, as 

 models are developed as replacements/substitutes for whole animal toxicology models, they will need to be thoroughly evaluated before they are accepted and implemented, and the associated whole animal toxicology model discontinued.

One of the main challenges facing the use and implementation of these alternate assays/methods is the validation/predictiveness of these alternate assays/methods. Acceptance of the assays/methods as a substitute by regulatory agencies and by the public will be based on researchers being able to demonstrate that the alternative assays/methods are equivalent or better at predicting human toxicity then the current whole animal toxicity models and that the outcomes of these assays/methods can be used to make drug development decisions that will protect patients and not jeopardize human health and safety.

Additionally, with the concerns about rising drug costs and cost of developing new therapies, researchers will need to be aware of the costs of implementing these alternate assays/methods. Current estimates to develop a drug range from $944 million to as high as $4.54 billion (5). If the cost of these alternative assays/methods substantially increases the cost of a drug’s development, companies will need to acknowledge these costs and still be supportive of these alternative assays/methods.

In the end, the development, implementation, and use of these alternative assays/methods will be a balance of how these assays/methods will decrease drug development timelines, how much faster can needed medicines get to patients, how much better they are at predicting human safety, and the value that these investments/costs bring to the drug development process.

, 31 (1) 19.1.1–19.1.35 (2007).
2. G.A. Van Norman, 

J. Am. Coll. Cardiol. Basic Trans. Science

, 4 (7) 845–854 (2019).
3. G.A. Van Norman, 

, 5 (4) 387–397 (2020).
4. M.N.H. Khabib et al., 

, 465, 153053 (2022).
5. M. Schlander et al., 

Felicity Thomas is the European editor for Pharmaceutical Technology Group.

Toxicology studies are an important and required aspect of drug development that are performed to ensure that drugs are deemed safe prior to patient administration and use in clinical trials.

Predicting Toxicity in Drug Development

IonSense, a US-based provider of direct analysis in real time mass spectrometry (DART) for rapid mass spectral analysis, has been selected to have its DART-MS technology used as part of the “Rapid Analysis of Drugs” program, a new drug screening program that is being piloted in five states across the United States. The pilot program is being used to test drugs and drug paraphernalia by utilizing the high-accuracy, fast detection mass spectrometry capability enabled by IonSense’s DART technology to identify the contents of drugs within minutes at the point of need.

The screening program was first launched by the Governor of Maryland, in conjunction with the Maryland State Police, Maryland Department of Health, and National Institute of Standards and Technology in December 2021, to identify illicit drugs and counter recent increase in overdose deaths. The program has also been adopted by four further states with Alabama, Virginia, Texas and Washington DC implementing the scheme and more states expected to follow in quick succession, according to a Jan. 13, 2022 press release.

DART is an ionization source that uniquely analyzes a variety of particles (including solids, liquids and gases) without the need for sample preparation, which removes a major time-consuming step, allowing users to rapidly identify samples, including many that do not ionize well, at the point of need.

New Technology

IonSense’s DART-MS technology offers rapid drug analysis without the need for sample preparation.

IonSense’s DART-MS Technology Selected for New Drug Screening Program

Texcell—North America, part of the Texcell Group of biosafety contract research organizations (CROs), is expanding its capabilities in customized R&D cell culture, good laboratory practice viral clearance studies, and select good manufacturing practice assay capabilities for viral safety testing with the construction of a new laboratory facility in Frederick, Md. The multimillion-dollar facility, which broke ground in December 2021, will add 27,000 ft2 of laboratory and office space, which more than doubles Texcell’s current capacity. The facility is expected to be complete in the first quarter of 2023, the company stated in a Jan. 7, 2022 press release.

The new facility will house eight new independent client suites designed to be flexible based on the specific needs of the project and the client. The suites will be stocked with mobile equipment, including new pure chromatography systems (ÄKTA, Cytiva) and nanofiltration units, which can be transferred from suite to suite as necessary, according to Texcell in the press release. The facility will also offer scaled-down manufacturing models and offer the ability to transfer work on specific projects to a dedicated viral clearance team.

“Viral clearance and safety testing are an integral part of the development of biologics and gene therapies. This expansion will give us the opportunity to scale up our testing capabilities to meet the rising demand for these life-saving products,” said Jeff Schubert, president of Texcell—North America, in the press release. “As the number of candidate molecules in clinical pipelines continues to grow rapidly, this additional capacity permits us to provide research support to even more [clients].”

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Texcell North America’s new lab facility in Frederick, Md., will expand the CRO’s capabilities in R&D cell culture, viral clearance studies, and viral safety testing.

Texcell North America Builds New Laboratory Facility

Announced in January 2022, Refeyn’s SamuxMP mass photometer is designed to be used with only basic training. Intended for use in adeno-associated virus (AAV) analytics, it has a mass range tailored for AAV analysis and provides accurate results in less than five minutes from sample loading to final result. Combined with low-operational costs and a small footprint, the SamuxMP enables routine quantification of empty/full AAV capsid ratios, even in smaller labs, to set a new standard in AAV characterisation.

According to a company press release, the SamuxMP is designed to overcome the drawbacks of the current analytical methods by enabling users to rapidly and cost-effectively determine empty/full capsid ratios for AAVs of any serotype at the bench using very low sample volumes and concentrations with minimal sample preparation. This is intended to enhance productivity and speed up workflows through more frequent analyses in-house, making R&D and process development of gene therapies and AAV-based therapeutics significantly more efficient.

“We are delighted to announce the launch of our SamuxMP mass photometer for fast, accurate, and accessible AAV analysis”, said Anthony Fernandez, CEO, Refeyn, in the press release. “Mass photometry provides an opportunity to overcome the analytical bottleneck in the gene therapy sphere for AAV-based therapeutics and we wanted to develop an instrument that would enable a real gain in efficiency. The SamuxMP delivers precise results from the bench whilst reducing cost and preparation time. It will enable researchers to focus on what they do best, and make AAV analytics just another part of their day-to-day workflows. We look forward to working with the bioscience research community to continue delivering innovative instruments that will simplify biomolecule characterisation.”

Refeyn’s SamuxMP enables routine quantification of empty/full AAV capsid ratios, even in smaller labs, to set a new standard in AAV characterization

Refeyn Announces SamuxMP for AAV Characterization

PhoreMost, a UK-based biopharmaceutical company, has formed separate partnerships with Polaris Quantum Biotech (POLARISqb), a US-based quantum computing drug design company, and NeoCura Bio-Medical Technology (NeoCura), an RNA-based drug research and development company headquartered in China, to study and discover new oncology therapies.

The POLARISqb Tachyon quantum computing platform will be used to scan billions of molecules from a large chemical space to find novel molecules that can be developed into drugs, based on information obtained from PhoreMost’s SITESEEKER phenotypic screening platform, a novel target-identification platform, according to PhoreMost in a Jan. 5, 2022, company press release.

SITESEEKER rapidly identifies unexpected or “cryptic” druggable sites across an entire genome, and PhoreMost, in collaboration with POLARISqb, will use the platform to identify oncology targets previously considered undruggable. This identification will be conducted using the inherent shape diversity and disease functionality of the PROTEINi (based on protein interference) protein-fragment libraries in live cells.

POLARISqb has built a drug discovery platform using Tachyon, a quantum computer that has the potential to significantly shorten the drug discovery process, according to the press release. With the use of quantum computers, POLARISqb can perform combinatorial optimizations in minutes that would take conventional supercomputers months or years to complete. The use of quantum computers leads to reduced drug development timelines and more efficient research, PhoreMost stated in the press release.

“This partnership represents the ultimate ambition for any collaboration between biology and technology, where the full diversity of newly identified druggable disease targets generated by biological PROTEINi shape-libraries can now be married to the most logical and rapid method of finding small-molecule drugs to them. This best-in-class intersection of biotech and AI [artificial intelligence] is going to be an exciting and transformative milestone for the entire pharmaceutical industry,” said Chris Torrance, CEO, PhoreMost, in the press release.

Under the NeoCura collaboration, PhoreMost will use its SITESEEKER platform together with NeoCura’s full-process RNA drug design platform to investigate the cellular delivery and efficacy of encoded targeted peptides. This research aims to inform and advance the research and development of innovative anti-cancer therapies.

“It is believed that with the … RNA drug research and development capability of NeoCura and … SITESEEKER technology of PhoreMost, more therapeutic potential will be released in the field of research and development of RNA drugs, and the translational process of anti-cancer drugs will be greatly accelerated. Meanwhile, NeoCura also hopes to join hands with more industry leaders in the vigorous development of biomedicine in China,” said Wang Yi, founder and CEO of NeoCura, in a Jan. 11, 2022, press release.

“NeoCura’s platform complements PhoreMost’s capabilities to unmask cryptic druggable sites across the entire human proteome. RNA delivery of novel therapeutics represents an exciting opportunity for PhoreMost as we aim to significantly increase the diversity and affordability of novel therapeutics for cancer and other unmet diseases,” said Torrance in the press release.

PhoreMost has entered into separate collaboration agreements with Polaris Quantum Biotech and NeoCura Bio-Medical Technology to discover and develop novel cancer therapeutics.

PhoreMost Collaborates with Polaris and NeoCura on Cancer Therapeutics

Following their July 2021 merger, Protagen Protein Services, BioAnalytix, and GeneWerk announced on Jan. 12, 2022 that their unified operations and re-branded name is ProtaGene, a contract research organization for the biopharmaceutical and cell and gene therapy industries.

The three legacy companies' combined synergy provides advanced, integrated, and complete protein and gene analytic services for biological therapeutics and cell and gene therapy platforms. ProtaGene provides services from discovery to commercialization.

Previously, Protagen Protein Services and BioAnalytix merged in April 2019, and GeneWerk, which specializes in vector safety, integration site analysis, and bioinformatics, was combined with the group in 2021.

"We are very excited to launch ProtaGene. The track record and reputation of the three legacy entities are individually impressive, and their combination into a single, globally integrated business delivers significant compounded value for our sponsors," said Martin Blüggel, CEO of ProtaGene and the founder of Protagen Protein Services, in a company press release.

"By combining our capabilities, platforms and knowledge, we can now provide our US-based biopharmaceutical and gene therapy customers advanced access to the broadest analytical offering from discovery to market, from a single vendor relationship," said Kirtland Poss, CEO-US of ProtaGene and the founder of BioAnalytix, in the press release.

"Our unique experience in gene analytics—especially integration site analysis, vector purity, vector copy numbers, and bioinformatics analysis for preclinical development and clinical trials—will support many innovators in taking breakthrough therapies to the clinic," added Annette Deichmann, senior vice-president of Cell and Gene Therapy at ProtaGene and the co-founder of GeneWerk, in the press release.

After a previously announced merger, Protagen Protein Services, BioAnalytix, and GeneWerk have formed a new CRO under the name ProtaGene.

Protagen Protein Services, BioAnalytix, and GeneWerk Combine to Form New CRO, ProtaGene 

Shanghai Fosun Pharmaceutical (Fosun Pharma), a China-based healthcare group, and Insilico Medicine, a US-based artificial intelligence (AI)-driven drug discovery and development company, announced on Jan. 11, 2022 that they have entered into a collaboration agreement to advance the discovery and development of drugs targeting a number of different targets globally using AI technology.

The partnership includes an AI-driven drug discovery R&D collaboration on four biological targets as well as the co-development of Insilico’s glutaminyl-peptide cyclotransferase-like (QPCTL) program. Under the agreement, Insilico will receive a total upfront payment of $13 million for the four R&D collaboration projects and the co-development of the QPCTL program. Insilico will also receive potential milestone-based payments and share commercialization profits from the QPCTL program. Fosun Pharma will also make an equity investment in Insilico.

Through the collaboration, Insilico will combine its end-to-end AI-driven drug discovery platforms with Fosun Pharma’s clinical development and commercial expertise. Their goal is to discover and develop a portfolio of novel therapeutics. According to the agreement, Insilico will take responsibility for delivering a preclinical candidate for the QPCTL program and advancing it to the investigational new drug (IND) stage (via its R&D team). After that, Fosun Pharma will conduct human clinical studies and co-develop the candidate globally. Fosun Pharma’s R&D team will also nominate four therapeutic targets to be assessed by Insilico’s AI platform and R&D team in parallel programs.

In addition, as part of the collaboration, Fosun Pharma will gain access to Insilico’s PandaOmics and Chemistry42 platforms to advance its own internal AI-powered discovery and development efforts.

“We are pleased to enter into strategic collaboration with Insilico. Fosun Pharma is committed to promoting innovative R&D and is oriented towards fulfilling unmet clinical needs and improving products’ accessibility. We look forward to working with Insilico to leverage the technological and clinical development strengths of both companies, jointly improving the efficiency of innovative drug R&D and benefiting more patients worldwide," said Yifang Wu, chairman and CEO of Fosun Pharma, in a company press release.

“In partnering with Fosun Pharma, a leading pharmaceutical company, we begin a new era of AI-powered end-to-end drug discovery and development as human-machine collaboration becoming the new normal in precision drug discovery and development. We previously demonstrated that AI can be used to discover novel targets and generate novel molecules that can be tested in humans in record time. Now, we are partnering with one of the leading scientific teams in the pharmaceutical industry to take this technology to the next level for the benefit of patients worldwide,” said Alex Zhavoronkov, founder and CEO of Insilico Medicine, in the press release.

Fosun Pharma and Insilico Medicine will collaborate on AI-driven drug discovery and development of product candidates targeting multiple disease targets.

Fosun Pharma and Insilico Medicine Partner on Drug Discovery and Development Using Artificial Intelligence

Fujifilm Diosynth Biotechnologies is expanding its BioProcess Innovation Center in Research Triangle Park (RTP), N.C., the company announced in a Jan. 5, 2022 press release.

The project, which will feature an additional 89,000 ft

 of laboratory space equipped with state-of-the-art analytical instrumentation, high throughput bioprocessing equipment, and automation technologies, is expected to double the company’s capacity to support process characterization programs and complements the enhanced capabilities at its UK facility. This expansion will also allow Fujifilm Diosynth Biotechnologies to further support its partners in guiding clinical process development that can create more robust commercial processes. 

The expanded space is expected to be operational by mid-2024, which is also when approximately 145 new jobs are anticipated to open up, many of those positions being for researchers and scientists.

“ … We are delighted to be adding this additional capacity to support our growing pipeline of customers,” notes Christine Vannais, chief operating officer, Fujifilm Diosynth Biotechnologies, RTP, North Carolina, in a company press release. “The cutting-edge laboratory equipment and automation tools, combined with the deep technical expertise of our scientific community, will allow us to better serve our partners to rapidly generate and assess data to understand complex molecules, along with the processes used in their manufacture.”

Fujifilm Diosynth Biotechnologies' 89,000 square-foot expansion of its BioProcess Innovation Center in Research Triangle Park, N.C., will double its capacity to support process characterization.

Pharmaceutical Technology's In the Lab eNewsletter, February 2022