Best Practices in Clinical Pharmacology Gap Analysis

A clinical pharmacology gap analysis is an essential step in optimizing drug development, regulatory submission and post-marketing surveillance. By identifying missing, incomplete or insufficient data in a clinical pharmacology profile, we can prioritize actions to meet regulatory expectations, improve safety and enhance therapeutic effectiveness.

Creating a clinical pharmacology strategy involves assessing a sponsor’s development program across multiple domains. 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 the 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. This considers the questions that the agency will ask about your clinical pharmacology data package at the time of an NDA submission. This exercise 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. This analysis also ensures that your NDA will contain all the elements needed to support review and informative, actionable product labeling.

In addition to identifying gaps and hot spots, a clinical pharmacology development strategy is created to ensure that each of the relevant domains is covered, that gaps are properly addressed, and that data are 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.

A group of researchers from the US FDA, academia, and industry wrote a paper articulating how clinical pharmacology methods and quantitative frameworks can improve the efficiency of drug development and evaluation.¹ Their 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

Clinical pharmacologists 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 reduce uncertainty related to therapeutic targets, dosing, and patient populations in which the novel compound may have the most efficacy.¹

Clinical pharmacology outcomes comprise about 50% of a drug label. Their importance in drug development and clinical decision-making is undisputed. These principles guide our approach to gap analysis.

FDA’s Center for Drug Evaluation and Research, Office of Clinical Pharmacology (OCP) provides 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 impairment)

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 subpopulations. The OCP review also identifies critical gaps in the understanding of conditions for optimal therapeutic use. OCP reviewers will then recommend studies that can address those gaps. Established and evolving regulatory policies and practices guide OCP recommendations.²

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 align with the sponsor’s overall clinical development plan. In addition, it considers strategies to support breakthrough therapy applications and accelerated versus regular approval pathways.

In all scenarios, the gap analysis and strategic plan identifies and mitigates risks which could become either decision-making hurdles during development or regulatory hurdles at the time of approval.

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 costs, 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 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. Clinical pharmacologists can perform gap analysis in early drug development, in advance of the IND submittal, in mid-development, either for the End of Phase 1 or End of Phase 2 meeting. While an early assessment is preferable, gap analysis can also be done later in development, as a company prepares the NDA or BLA submission.

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 the FDA, EMA, and MHRA and 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 integration of MIDD and other technologies. We’ve sat on both sides of the table at critical regulatory meetings. Thus, we’re 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 400 label claims without the need for clinical studies.

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 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. Our experts help 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 helps identify biological pathways and disease determinants.
• Quantitative Systems Toxicology (QST) — QST modeling combines toxicity and ‘omics’ data to focus on drug 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 – Our writers employ a rigorous, quality-driven process of regulatory documentation and communications support from discovery through life-cycle management.

A clinical pharmacology gap analysis is not just a compliance checklist. It is a strategic tool to reduce regulatory risk, optimize trial design, improve patient safety and accelerate time to market. By following these best practices, defining scope, engaging cross-functional expertise, mapping to regulatory expectations, prioritizing gaps, using modeling and simulation and keeping the analysis dynamic, you can transform potential weaknesses into opportunities for stronger submissions and better patient outcomes.

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 visit this page.