Sarfaraz K. Niazi, PhD, explains the FDA's changes to the drug review process, the significance of each change, and the published pieces of work that helped inform the FDA's decisions.
The FDA has always been proactive in bringing science ahead of archaic regulatory beliefs; one example is the FDA's Division of Applied Regulatory Science (DARS), which conducts multidisciplinary studies to answer scientific questions and solve regulatory challenges, leading to modifications in the regulatory guidelines. Recently, the DARS' 21 top scientists published a pivotal paper summarizing some of their recent achievements based on the plans for 2021, many of which will impact the development of biosimilars. I had the privilege of serving as a reviewer of this paper.
The capabilities within the DARS include laboratory-based research specializing in omics, bioanalysis, micro-physiological and cellular systems, immunology, electrophysiology, and silico research performed by informatics and computational modeling groups. In addition, DARS conducts clinical research focused on facilitating new and biosimilar/generic drug development and assessing the safety of marketed drugs.
Finally, using applied research, DARS investigates questions related to clinical pharmacology, medical toxicology, systems pharmacology, chemistry, and biology.
The following projects were discussed in the paper:
Expediting Biosimilar Development
Bringing more drug competition to the market and addressing the high cost of medicines is a priority for the FDA and the HHS, an effort exemplified by the Drug Competition Action Plan in2017 and the Biosimilars Action Plan in 2018. These plans outlined concrete steps the FDA would take to remove barriers to biosimilars and generic drug development, including prioritizing biosimilar applied research projects.
Immunogenicity of Biosimilars
A factor influencing the rapid development of biosimilars is the ability to predict the potential risk of a stronger immune response (immunogenicity) in humans to a proposed biosimilar than that seen with the innovator product.
For most biosimilars, this is still assessed through clinical trials. DARS is studying the ability of nonclinical approaches to predict immunogenicity risk without conducting a clinical trial. This includes assessing specific in vitro assays and cell types, in vivo models, and identifying valuable controls. These methods have the potential to identify products with immunogenicity risk sooner and streamline the development of biosimilars and certain complex generic drugs.
DARS compares theabilityofdifferent nonclinical models to predict immune-mediated adverseeventsfrombiologicaldrugproducts. For example, DARS has testedtheuse of novel nonclinical models to predict cytokine release syndrome, a potentially life-threatening complication associated with biological products, and showed that nonclinical models could effectively demonstrate this adverse event.,
Additionally, after successfully demonstrating immune-mediated activation in a nonclinical model, investigations continue for checkpoint inhibitor oncology treatments for which adverse events cannot be predicted using computational, in vitro, or conventional nonclinical methods.
Since the (PHASE) can be used to predict the activity of new proteins and identify their immunogenicity, in silico models that demonstrate similarity should also show similar activity and immunogenicity. For example, the 3-dimensional (3D) structure of proteins depends entirely on the primary amino acid sequence. So, if a biosimilar candidate has the same sequence, why should its 3D structure differ from the reference product? Since the 3D structure is entirely responsible for activity (receptor binding) and immunogenicity, why should a biosimilar candidate not be the same and require additional testing?
DARS significantly focuses on leveraging molecular target information to predict safety issues. Knowing a drug’s molecular targets can identify a drug’s effects and potential safety concerns early. DARS leads multiple efforts collating information about a drug’s known and predicted targets to identify potential safety concerns.
For example, DARS developed multiple computational methodologies, including machine learning, to predict a drug’s adverse effects based on the biological receptors that the drug, or similarly structured drugs, are known to target. These computational methodologies demonstrated promising performance in predicting significant adverse events. These results may indicate which organ systems and adverse event categories to closely monitor during clinical trials or clinical and nonclinical data review.
Additionally, DARS is analyzing and building a database for secondary pharmacology activity submitted by the industry as part of their Investigational New Drug Application. A drug developer typically conducts in vitro target binding and functional assays for 80 to 100 biological receptors to determine potential on-target and off-target effects. However, the targets chosen for the assays and submission format are not currently standardized across the industry.
Therefore, data from these assays have been manually extracted and curated into a database to allow easier access to and analysis of these study results. Additionally, DARS is engaging in a public-private partnership with the Pistoia Alliance to determine the best methods for future regulatory submission of these studies.
Many of DARS’ current initiatives demonstrate the FDA's thinking on using pharmacodynamic (PD) biomarkers to demonstrate biosimilarity that may streamline or negate the need for comparative clinical studies (Figure). This included conducting 3 clinical studies to define best practices for characterizing PD biomarkers for different classes of drugs and to develop general considerations applicable to all types of biomarkers for biological products.,,
These studies included assessments to evaluate the uses of proteomic and transcriptomic analysis of human plasma to identify novel biomarkers for biosimilar development. In addition, a joint FDA/Duke Margolis Workshop discussed initial findings and facilitated a broader discussion on using PD biomarkersfor biosimilar development. In the journal Clinical Pharmacology and Therapeutics, additional details are reported in the January 2023 themed issue on Innovations in Biosimilars.
Impurities and Extractable/Leachable Compounds
The growing use of (Q)SAR models for the safety assessment of drug products led to the formation of the DARS Computational Toxicology Consultation Service. In addition, the ICH M7(R1) international regulatory guideline recommends using (Q)SAR predictions as a state-of-the-art alternative to experimental testing to qualify a drug impurity for mutagenic potential.
Extractable/leachable compounds constitute a significant concern for biosimilars as these might alter the immunogenicity profile that arrives from manufacturing, packaging, drug delivery, and/or container closure systems. For non-mutagenic compounds with limited general toxicity data, a manual structure-activity relationship, or “read-across,” assessment based on structurally similar surrogate compounds may inform setting a permissible daily exposure limit. DARS staff review applicants’ proposed surrogates for extractable/leachable compounds and, if needed, recommend alternative surrogates based on structural, metabolic, and physicochemical considerations.
I wish to thank the FDA's DARS program for removing redundant testing that only adds cost and time to the approval of biosimilars; without such actions, making biosimilars affordable may not be possible. Incidentally, the term dars means "lesson" in Persian and Arabic.
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