Do you get anxious about taking tests? Many people do because they want to show their best efforts.
Submitting your New Drug Application (NDA) to the FDA can be thought of as the ultimate test of a drug program. Are you confident that you’ll have robust answers to the 40 different questions that the agency will ask about your clinical pharmacology data package at the time of a NDA submission? If the thought gives you “pre-test jitters,” you might want to invest in clinical pharmacology gap analysis—a tool that can help you evaluate and address any potential gaps in your program before the FDA does.
What is gap analysis?
Creating a clinical pharmacology strategy involves assessing a sponsors’ development program across multiple domains to craft a strategy to address each. For a target product or program, the strategy includes the following elements:
- Identifying potential R&D or regulatory challenges, custom to the molecule, therapeutic area, and competitive landscape,
- Ensuring integration of pre-clinical findings with planned clinical programs,
- Creating a clinical pharmacology development program in line with anticipated regulatory filing strategy,
- Identifying and leveraging pharmacometrics and other model-informed drug development technologies that will increase speed and efficiency,
- Guiding interactions with regulatory agencies for research programs and submittals.
The first step in a strategic assessment is a gap analysis. In conducting a program gap analysis, we consider the 40 different questions that the agency will ask about your clinical pharmacology data package at the time of a NDA submission. This allows one to evaluate and address any potential gaps before the FDA does at critical milestones such as End of Phase 1 (EOP1), EOP2 or Pre-NDA while ensuring that your NDA will contain all the elements needed to support review and informative actionable labeling for your product. In addition to identifying gaps and hot spots, a clinical pharmacology development strategy is created to ensure each of the relevant domains are covered, that gaps are properly addressed, and that data is gathered at meaningful times to enhance decision-making during development. While best conducted early, a gap analysis provides unquestionable ROI at any stage of development.
Reducing the uncertainty of drug development
A group from the US FDA, academia, and industry recently wrote a paper articulating how clinical pharmacology methods and quantitative frameworks can improve the efficiency of drug development and evaluation.1 That 2017 Clinical Pharmacology and Therapeutics paper, “Improving the Tools of Clinical Pharmacology: Goals for 2017 and Beyond,” attributes the limitations in drug development to scientific challenges in predicting efficacy and safety or characterizing sources of response variability for a drug compound at early, less expensive stages of discovery.1
The field of clinical pharmacology can help stakeholders address these challenges and improve decision-making at critical milestones, whether early in proof-of-concept phases (pre-clinical through 2a) or in the later stages where a more robust risk and efficacy profile is established (2b through 3). The tools, methods, and frameworks (e.g., mechanistic or quantitative) of clinical pharmacology span distinct sub-specialties and can significantly impact these pre-clinical and clinical phases. They can greatly reduce uncertainty related to therapeutic targets, dosing, and patient populations in which the novel compound may have the most efficacy.1
Clinical pharmacology comprises about 50% of a drug label. Its importance in drug development and clinical decision-making is undisputed. These principles guide our approach to gap analysis.
The clinical pharmacology review process
FDA’s Center for Drug Evaluation and Research, Office of Clinical Pharmacology (OCP) recently updated its Manual of Policies and Procedures (MAPP) Good Review Practices for New Molecular Entities (NME), New Drug Applications (NDAs), and Original Biologics License Applications (BLAs). The MAPP includes guiding principles for the OCP integrated review, specific templates and sections for review, a guide for labeling issue identification, and a clinical pharmacology and pharmacometric summary table. OCP reviewers use the Question Based Review (QBR) outlined in the MAPP to guide NDA and BLA reviews.
Clinical pharmacology is a multidisciplinary science. Thus, OCP reviews of NME NDAs and original BLAs synthesize information from relevant areas including drug disposition, pharmacology and biomarkers, quantitative methods, drug safety, drug efficacy, pharmacotherapy, and clinical trial methods to inform regulatory decisions (e.g., approvability, labeling, post-approval requirements, and product lifecycle management). Pharmacometric analyses are a key component of each question in the OCP QBR and are used to provide:
- Support of drug activity
- Identify subsets of patients with notably large treatment benefits or favorable risk/benefit balance or a drug with significant toxicity or otherwise marginal average treatment effects
- Support of a single adequate and well-controlled clinical trial using dose-response and/or exposure-response trends
- Support the dosing regimen
- Identify intrinsic factors that influence exposure and/or PD of the drug
- Support dosing strategy based on modeling and simulation
- Justify dosing for subgroups and specific covariates (age, weight, renal/hepatic)
The OCP review is issue-driven and assesses information in the applicant’s submission with established knowledge to address dose selection and optimization, therapeutic individualization, and benefit/risk balance for the general population and for subpopulations. The OCP review also identifies critical gaps in the understanding of conditions for optimal therapeutic use and recommends studies that can address those gaps. Established and evolving regulatory policies and practices guide OCP recommendations.2
The purpose of gap analysis
We help position sponsors for successful interactions with regulators and other partners by creating for them a clinical pharmacology and pharmacometrics roadmap that prioritizes needs, provides strategic direction, identifies gaps, and assesses risk/benefits. The strategic plan will be harmonized with the sponsor’s overall clinical development plan and considers strategies to support breakthrough therapy applications and accelerated versus regular approval pathways. ギャップ分析および戦略的計画の策定によって、開発中の意思決定に関するハードル、または承認時の規制対応に関するハードルと成り得るリスクをあらゆる状況において明らかにするとともに、軽減させることが可能になります。
A gap analysis begins with evaluating all available data and information on the compound, including the Target Product Profile (TPP), Investigator’s Brochure, clinical study plans, any regulatory meeting minutes, and all available pre-clinical and clinical technical data. A gap analysis report will outline the clinical pharmacology program needs, assess which dedicated studies are needed and why, and recommends the use of pharmacometrics and other quantitative methods to expedite timelines, reduce cost, and minimize clinical studies wherever possible.
Questions asked and answered in a gap analysis include:
- Will the completed or planned studies support the OCP question-based review (QBR) and labeling?
- Are the data collected sufficient to support planned analyses?
- Does the quality of existing data, analyses, study designs, and overall clinical approach support the desired regulatory strategy?
- Are we leveraging the ‘best’ science and technology available?
- Does the data support the goals of the TPP?
- Is more evidence needed? If so, is it better to obtain this evidence through standalone studies or through quantitative analyses?
The gap analysis summary report will provide the sponsor with a plan to address any clinical pharmacology gaps and recommend strategies for submitting a data package for regulatory approval. Gap analysis can be performed in early development, in advance of the IND submittal, in mid-development, either for the End of Phase 1 or End of Phase 2 meeting, or later in development, as a company prepares the NDA or BLA submission.
The return on Investment (ROI) of gap analysis
A gap analysis provides a roadmap for success, translates model-informed drug development (MIDD) into the decision-making process, and identifies ways to either support or supplant clinical studies. The areas for which MIDD can be leveraged include drug-drug interaction (DDI) strategy, the approach to support dose justification based on pharmacokinetic/pharmacodynamic (PK/PD) and exposure response, the strategy to meet evolving requirements for QTc assessment, the plan for addressing special populations (renal/hepatic impairment), and opportunities for pharmacogenomics. Our staff of 550 professionals has years of development experience in FDA and in both large and small pharma. They are eminently capable of performing these analyses. While maintaining regulatory standards, we create efficiencies through better study designs and integrating of MIDD and other technologies. Because we’ve sat on both sides of the table at critical regulatory meetings, we are confident in our recommendations. Typically, the ROI for this analysis is 10-20x, and frequently 50-100x or more, depending on the program. The ROI includes reduced study size, expedited timelines, and studies that can be replaced by MIDD. For example, our work in physiologically-based pharmacokinetics (PBPK) has achieved more than 100 label claims without the need for clinical studies.
Modeling & simulation: a “useful predictive tool”
Understanding and selecting the correct tool to answer key drug development questions and optimize decision-making is key. Our portfolio of tools in performing a gap analysis and recommending a strategic roadmap include:
- Drug Development and Regulatory Strategy Consulting – As the industry migrates from a ‘best in class’ to a ‘best in value’ perspective, sponsors’ scientific, regulatory and commercial strategies must be well-aligned. An integrated decision support system focuses on increasing confidence, understanding all aspects of safety and efficacy, optimizing cost and development time, and guiding development using model-informed drug discovery and development (MID3).
- Pharmacometrics Modeling – Population PK, exposure-response and disease-state modeling are used to predict clinical outcomes, provide support for dose recommendations, justification and modification, assess trends for safety and efficacy across exposure ranges, and inform ‘go/no go’ decisions.
- PBPK – PBPK technology informs key R&D decisions related to clinical trial design, informs first in-human dosing, formulation design, dosing in special populations, and predicts the likelihood of DDIs.
- Clinical Pharmacology – Accounting for about 50% of a drug label, clinical pharmacology approaches can reduce late-stage attrition and increase pharma R&D productivity. Expertise in this discipline allows drug developers to reduce uncertainty related to therapeutic targets, dosing, and the patient populations in which the novel compound may have the most efficacy.
- Quantitative Systems Pharmacology (QSP) – This emerging mechanistic modeling approach focuses on target exposure, binding and expression. It is employed to identify biological pathways and disease determinants.
- Quantitative Systems Toxicology (QST) – QST modeling combines toxicity and ‘omics’ data to focus on modes of action and adverse outcome pathways.
- Model-based Meta-analysis (MBMA) – Proprietary, curated databases of publicly-available trial information are used to develop models that compare a drug’s effectiveness against competitor products, optimize clinical trials, scale from biomarker to endpoint and inform marketing decisions.
- Strategic Regulatory Writing and Communications – A rigorous, quality-driven process of regulatory documentation and communications support is employed from discovery through life-cycle management.
You should now have a better understanding of what gap analysis is and how it can benefit your drug program. To learn more about using a strategic, programmatic approach to drug development, please watch this webinar by my colleagues, Drs. Craig Rayner and Patrick Smith.
 Zineh, et al. “Improving the Tools of Clinical Pharmacology: Goals for 2017 and Beyond,” Clinical Pharmacology and Therapeutics, January 2017
 FDA Office of Clinical Pharmacology, Manual of Policies and Procedures, Good Review Practices: Clinical Pharmacology Review of New Molecular Entity (NME), New Drug Applications (NDA), and Original Biologics License Applications (BLAs), September 2016