Clinical Pharmacology Deep Dive

Clinical Pharmacology investigates the interaction between drugs and humans.

The dimensionality of the field is immense. Check out the table below to navigate through the drug development cycles and assess how clinical pharmacology impacts drug development.

  • Discovery to FIH
  • FIH to PoC
  • PoC to Registration
  • Registration
  • Lifecycle Management



Impact on Drug Development

Predict exposure-response relationship in humans.

  • Utilize PK/PD data from preclinical models to inform candidate selection and developability to FIH.
  • Estimated therapeutic dose range for humans.

Propose relevant dose range and design for FIH.

  • Model-predicted human PK.
  • Estimation of Minimum Anticipated Biological Effect Level (MABEL) and toxicological coverage for humans.
  • Estimate safe starting dose for humans.
  • Ensure that the proper dose range is studied.

Assess clinical drug-drug interaction (DDI) potential.

  • Preclinical drug metabolism data.
  • A qualitative prediction of clinical DDIs.
  • A quantitative prediction of clinical DDI magnitude.
  • Provide development strategy for clinical DDI studies and inclusion/exclusion of key con-meds in clinical trials.

Benchmark competitor compounds for precedented MOA (through development)

  • Meta- or a descriptive-analysis of relative potencies, therapeutic indices, DDI
  • Differentiate compound against key competitors.

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Impact on Drug Development

Inform dose escalation and repeat dose decisions in human subjects.

  • NCA PK analyses.
  • Evaluation of systemic exposure and variability.
  • Determine steady-state and dose proportionality of systemic exposure.


  • Exposure in humans relative to pharmacologic target and toxicological risk informs appropriate dose escalation.
  • Estimate variability in systemic exposure.

Characterize the clinical PK in healthy subjects and/or patients

  • NCA PK analyses.
  • Population-PK-model of exposure and variability.
  • Early evaluation of potential inter-ethnic differences.
  • Sampling strategies for population PK-PK/PD analyses.
  • Determine early sources of variability in exposure.
  • Evaluate potential differences between healthy subjects and patients.

Provide rationale for dose regimen(s) for PoC studies.

  • Identify relationship between exposure and response to select appropriate dose regimens.
  • Estimate key parameters of pharmacological response.
  • Conduct model-based analysis of exposure-response, PK and drivers of variability.
  • Predictions of therapeutic index.
  • Enhanced understanding of benefit and risk and increase chances of a successful PoC.

Advocate for innovative trial designs

  • Model-based trial simulations including key drivers of outcome.
  • Adaptive trial design simulations.
  • Exposure-response power estimates
  • Non-traditional endpoint evaluations.


  • Improved drug development decisions using model-based simulations of the drug- and disease-time course

Initial evaluation of the risk of potential DDIs and Food Effect (FE)

  • Rationale (PK or PD), design, dose rationale, and interpretation of appropriate DDI studies
  • Recommend appropriate doses for future studies.

Initial assessment of QTc risk

  • Meta-analysis of concentration-QTc data from Phase 1/2a
  • Estimate QTc-risk potential to inform development strategy

Inform Pediatric Investigation Plan (PIP)/strategy

  • Pediatric development strategy. Exposure-response modeling to justify pediatric dose(s), study design(s) and PK sampling
  • Dose regimen(s) that provide optimal response for a range of ages and development groups  

Support EOP2a regulatory submission

  • Exposure-Response and Clinical Pharmacology sections of FDA End of Phase 2a briefing document and other global regulatory briefing documents
  • Regulatory review of rationale for dose regimen(s) based on exposure-response relationships,  Clinical Pharmacology strategy, Phase 2b study design

Inform and support formulation strategy

  • Apply modeling techniques (e.g. IVIVC) to predict in vivo performance of selected formulations.
  • Guide development of formulations to maximize the probability of success to deliver desired concentration-time profile in humans.

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Impact on Drug Development

Characterize the clinical PK in larger patient populations

  • Population PK analyses of Phase 2b and Phase 3 studies with identification of covariates
  • Determine sources (intrinsic and extrinsic) of variability in exposure in patient populations.

Innovative dose-ranging trial design proposal

  • Clinical trial simulation of predicted dose response and power to estimate EC50/ED50 and other key parameters
  • Predict outcome for various trial designs, patient populations, endpoints to inform optimal designs

Execute dose- and model-based meta-analysis of exposure- response for key efficacy/safety endpoints

  • Simulation strategy to support selection of optimal Phase 2b/3 dose(s)
  • Apply population modeling methods to characterize exposure-response for labelling


  • Enhanced understanding of benefit and risk.
  • Dose regimen(s) and trial designs that deliver safety and efficacy for a differentiated product for patients that maximizes benefit and reduces risk.
  • Avoid replicate trials

Support/design Phase 1 studies:

  • Definitive Food Effect
  • Drug-drug interaction studies.
  • Bioequivalence study (if necessary).

  • Identification of appropriate studies.
  • Rationale, design, analysis and interpretation of  PK
  • Identify appropriate dose and dose regimen for the appropriate patient population.

Conduct definitive assessment of QTc risk

  • Concentration-QTc analysis of thorough QTc study
  • Clinical QTc-risk defined

Support EOP2 regulatory submission

  • Clinical Pharmacology sections of the FDA and EMA briefing documents
  • Regulatory review of rationale for dose regimen(s), Clinical Pharmacology strategy, Phase 3 study design

Evaluation of special populations (e.g., renal/hepatic impairment)

  • Clinical PK evaluation of exposure in special populations
  • Model-based extrapolation of alternative dosing regimens


  • Recommend appropriate doses in special populations (e.g., renal/ hepatic impairment)

Assessment of demographic
and responder/non-responder differences in exposure- response

  • Population PK/PD analyses with identification of significant covariates that impact PK and/or response
  • Identify groups that demonstrate different efficacy or safety based on exposure-response relationships

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Impact on Drug Development

Deliver Clinical Pharmacology sections of global regulatory submissions (adults and pediatrics).

Enable registration in global markets
Enable use of non-EU/US data in EU/US

  • CTD Modules 2.7.1 and 2.7.2
  • Contribute to CTD Module 2.7.3 (dose justification) and Module 2.5
  • Labeling sections (i.e. PLR, PIL, GDS): Dosage and Administration, Drug Interactions, Use in Specific Populations, Clinical Pharmacology;  Clinical Studies/Contraindications/ Warnings/Precautions (as applicable)
  • Provide responses to regulatory questions pertaining to Clinical Pharmacology and dose
  • Clinical Pharmacology science (understanding of drug) and labelling optimal for appropriate use of medication in patients and for registration
  • Reduces / eliminates need for local studies, shortens approval times.

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  • Post-approval regulatory support
  • Provide responses to regulatory questions pertaining to Clinical Pharmacology, labeling [PLR, GDS], registration in additional countries, post-approval studies
  • Clinical Pharmacology science (understanding of drug) and labelling optimal for appropriate use of medication in patients
  • Alternative indications and routes of administration
  • Dose regimen(s) rationale based on exposure-response and model extrapolation
  • Sections of regulatory submissions (as above)
  • Efficient Clinical Pharmacology strategy for appropriate use of medication in patients
  • Guide new formulation strategy
  • Apply modeling techniques (e.g IVIVC) to guide new formulation clinical development strategy
  • Formulation delivers desired concentration-time profile in humans

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