Biologics Formulation
ATMP Formulation
developability-assessment-biologics
Navigating the complex path of biologic drug development presents numerous hurdles, with many candidates having challenges during manufacturing, costing millions. An early, robust CMC developability assessment acts as a critical risk mitigation strategy, significantly improving success rates.
Key Takeaways
Early developability assessment of biologics is a critical risk mitigation strategy, saving significant time and resources by identifying potential issues before major investment.
A comprehensive assessment evaluates multiple parameters including physicochemical properties, stability, and manufacturability.
Data-science methods and advanced analytical techniques are integral to modern developability assessment, enabling prediction of liabilities and guiding candidate selection.
Bringing a novel biologic to patients is a journey with an average investment often exceeding 1 billion Euros, compounded by high attrition rates. [1, 2] A significant number of biologic candidates encounter setbacks in later development stages due to not only clinical failure but also unforeseen issues related to their physicochemical properties, manufacturability, or stability. [3] Implementing a comprehensive developability assessment biologics strategy early in the discovery phase, before preclinical candidate selection, is no longer a luxury but a necessity. This proactive approach, utilizing a data-science formulation approach, identifies potential liabilities such as aggregation, poor solubility allowing for timely intervention and optimization. [4, 5] Such early insights save considerable resources and accelerate timelines by ensuring only the most promising and robust candidates progress. [6]
Defining a Robust Developability Assessment Framework
A thorough developability assessment for biologics encompasses a multi-faceted evaluation of a candidate's intrinsic properties. This typically involves analyzing over 100 different descriptors. [5] Key areas include physicochemical characterization, stability under various stress conditions (thermal, mechanical, photo-stress), and preliminary manufacturability evaluations. [2, 7] For instance, understanding a molecule's propensity for aggregation, which can be influenced by as few as 1-2 amino acid changes, is critical. [3] Many teams underestimate the impact of early, minor sequence modifications, which can improve yields by over 15%. This initial screening phase aims to identify red flags using as little as a few milligrams of material. [5] The developability assessment process provides a clear path to de-risk your biologic candidate. This systematic evaluation sets the stage for more detailed characterization if the candidate shows promise.
Key Parameters in Early-Stage Biologic Candidate Profiling
During the initial screening of hundreds of potential candidates, several key developability parameters are assessed. [3] These include, but are not limited to: solubility, aggregation propensity, thermal stability (e.g., melting temperature, Tm). [2, 5] Assessing molecule integrity and identifying risks such as degradation and aggregation are paramount; even a 5% increase in aggregation can render a candidate unviable. [2] Early stability indicators help select the best drug candidates. [2] For example, identifying post-translational modification hotspots or aggregation risks can be achieved with computational analysis even before extensive lab work. [3] Often, the focus is on affinity, yet a candidate with 10% lower affinity but 50% better stability is usually a superior choice. These initial checks, often requiring only micrograms to a few milligrams of material, are crucial for biologics drug development. Understanding these parameters early allows for informed decisions on which candidates warrant further investment for more detailed assessments.
The Role of Data-Science in Predicting and Mitigating Risks
Computational tools and data-science methods play an increasingly significant role in modern developability assessment of biologics. [3, 4] These approaches can predict potential liabilities with an accuracy often exceeding 70% for certain parameters. [4] For instance, in silico tools can identify aggregation-prone regions based on sequence and structural data. [4, 5] This allows for the ranking of candidates and can trigger protein engineering efforts to mitigate identified risks, potentially improving developability. [7] The benefits include:
Identification of potential chemical degradation motifs (e.g., oxidation, deamidation) with over 80% accuracy. [4]
Prediction of aggregation hotspots, guiding targeted amino acid substitutions.
Modeling of full-length antibody structures for more accurate property computation. [4]
Assessment of developability parameters like viscosity and solubility using minimal experimental data. [4]
Facilitating a Design of Experiments (DoE) approach for subsequent lab work.
A common oversight is not integrating computational data with initial, small-scale experimental results early enough, missing opportunities for rapid iteration that could save time. Such predictive power enables a more focused and efficient progression of biologic candidates.
Integrating Developability with CMC and Formulation Strategies
Developability assessment is not an isolated activity; it is intrinsically linked to Chemistry, Manufacturing, and Controls (CMC) and formulation development. [1, 6] Early developability data, such as solubility limits (which can vary by factors of 100 or more between candidates) and stability profiles, directly inform initial data-driven formulation science efforts. [2, 5] For example, a candidate prone to aggregation at pH 6 might require a data-science formulation approach targeting pH 7, potentially increasing stability by over 20%. [2] Understanding these characteristics helps in selecting appropriate formulations and processing conditions, aiming for a formulated drug substance with optimal stability and manufacturability. [2] It's a misconception that all developability issues can be 'formulated out'; some intrinsic molecular flaws identified early can save millions by halting a doomed project before significant CMC investment. The ICH Q5A (R2) guideline underscores the importance of well-characterized production processes, which begins with a developable molecule. [8] This holistic view ensures a smoother transition from candidate selection to robust manufacturing processes.
Analytical Techniques Supporting Comprehensive Developability Assessment
A suite of advanced analytical techniques underpins a successful developability assessment biologics program. [5] High-throughput assays are employed in early screening, while more detailed characterization is reserved for fewer, promising candidates. [5] Key techniques include:
Dynamic Light Scattering (DLS) for assessing aggregation propensity, capable of detecting aggregates as small as 1 nm. [5]
Differential Scanning Calorimetry (DSC) or Differential Scanning Fluorimetry (DSF) for determining thermal stability (Tm), with a precision of +/- 0.5°C. [2, 5]
Size Exclusion Chromatography (SEC-HPLC) for quantifying high and low molecular weight species, often detecting impurities at levels below 0.1%. [7]
Mass Spectrometry (MS) for confirming identity and detecting post-translational modifications with sub-ppm accuracy.
Capillary Isoelectric Focusing (cIEF) for charge heterogeneity analysis.
Assays for measuring solubility, often up to concentrations exceeding 100 mg/mL. [2]
In silico tools for sequence analysis and structural modeling, capable of screening hundreds of candidates in hours. [3, 4]
Focusing solely on a single stability-indicating parameter can be misleading; a 5 °C higher Tm might be irrelevant if the candidate shows poor solubility at the target concentration. Comprehensive biopharmaceutical analytical services are vital. These methods provide the critical data needed to build a complete developability profile for each biologic candidate, guiding selection and de-risking progression.
The primary goal of developability assessment biologics is risk mitigation, ensuring that only candidates with a high probability of success move forward. [1, 6] Identifying potential issues like immunogenicity, poor stability (e.g., a candidate losing 20% activity in 1 week under stress), or manufacturing challenges (e.g., titers below 1 g/L) early on prevents costly late-stage failures. [1, 2, 5] For instance, early predictive stability testing can highlight candidates requiring significant protein engineering, a process that can add 6-12 months to development if discovered late. [7] A surprising number of programs proceed with suboptimal candidates due to insufficient early developability screening, leading to later CMC hurdles. By integrating developability assessment from the earliest stages, companies can make data-driven decisions, selecting candidates that are not only efficacious but also possess the necessary attributes for successful protein stabilization and progression through preclinical and clinical development. This proactive approach is key to overcoming common formulation challenges. Ultimately, this leads to more efficient use of resources and faster timelines to deliver new therapies to patients.
The field of developability assessment for biologics is continually evolving, with new technologies and approaches emerging to handle increasingly complex molecules like bispecific antibodies and cell therapies. [4, 5] Data-science methods and machine learning are becoming more sophisticated, offering enhanced predictive capabilities for a wider range of developability attributes, potentially improving prediction accuracy by another 10-15% in the next 5 years. [4] Miniaturization and automation of analytical techniques are enabling higher throughput screening with even smaller sample volumes, perhaps reducing material needs by up to 50%. [5] There is also a growing emphasis on understanding the interplay between a biologic's properties and its interaction with the in vivo environment earlier in development. A key future challenge will be standardizing developability parameters across different novel modalities, as a 'one-size-fits-all' approach is often insufficient for molecules beyond traditional mAbs. These advancements promise to further de-risk biologic development, reduce attrition rates by an additional 5-10%, and accelerate the delivery of innovative medicines. [4, 6]
FAQ
What key parameters are evaluated during a biologics developability assessment?
A biologics developability assessment evaluates whether a molecule is suitable for formulation, manufacturing, and clinical progression. It includes in silico modeling to predict structural liabilities (e.g. aggregation, instability), benchmarking against successful molecules, and physicochemical screening to assess solubility, thermal stability, and aggregation under stress. These insights help flag risks early and guide development strategy. [2, 5]
At what stage should developability assessment for biologics be performed?
Developability assessment should ideally begin in the late drug discovery process, often during hit-to-lead selection or before preclinical candidate nomination, to maximize its impact on de-risking the project. [1, 4]
What is the impact of poor developability on CMC timelines?
Poor developability can lead to significant delays in CMC timelines due to the need for extensive re-engineering, difficulties in scaling up manufacturing processes, or stability issues, potentially adding months or even years to development. [1, 6]
Can all developability issues be resolved through formulation?
While advanced formulation strategies can address many stability and delivery challenges, some intrinsic molecular liabilities (e.g., very high aggregation propensity or inherent instability) identified during developability assessment may be too severe to overcome solely through formulation, necessitating earlier candidate deselection or re-engineering. [2]
How does Leukocare approach developability assessment?
Leukocare employs a data-science guided formulation approach, integrating advanced analytical techniques and predictive modeling to comprehensively assess biologic candidates. This allows for early identification of risks and the design of optimized, stable formulations to accelerate CMC timelines.
What are the consequences of skipping a thorough developability assessment?
Skipping a thorough developability assessment can lead to higher attrition rates in later development stages, unexpected manufacturing or stability problems, increased costs, and significant delays in bringing a biologic therapeutic to market. [1, 6]
References List
[1] Biologics Developability Assessment & Optimization: https://www.bioprocessintl.com/sponsored-content/critical-aspects-of-biologics-developability-assessment-and-optimization-in-early-r-d
[2] Pharmaron Developability Assessment Services: https://www.pharmaron.com/services/developability-assessment/
[3] The Key to Biologics Success: Why Developability Assessments Matter: https://cellculturedish.com/the-key-to-biologics-success-why-developability-assessments-matter-in-antibody-discovery/
[4] Ionic Liquids for Protein Formulation: https://link.springer.com/article/10.1007/s12551-024-01261-y
[5] Analytical strategies for developability assessment of therapeutic proteins: https://oak.novartis.com/35908/
[6] Biologics Developability Assessment & Optimization: https://www.wuxibiologics.com/perspectives-post/critical-aspects-of-biologics-developability-assessment-and-optimization-in-early-rd/
[7] Improving the Developability of Biopharmaceuticals: https://www.biocompare.com/Media/37/Document/Lonza-WhitePapers-Improving-Development-of-Biopharmaceuticals-30973.pdf
[8] ICH Q5A(R2) Guideline on Viral Safety: https://database.ich.org/sites/default/files/ICH_Q5A(R2)_Guideline_2023_1101.pdf
[9] FDA Biosimilars Guidances: https://www.fda.gov/vaccines-blood-biologics/general-biologics-guidances/biosimilars-guidances
