Brett Mazuka

  • CS to FTIH
  • FTIH to PoC
  • PoC to Registration
  • Registration
  • Lifecycle Management

Objectives

Tools/Deliverables

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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Objectives

Tools/Deliverables

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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Objectives

Tools/Deliverables

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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Objectives

Tools/Deliverables

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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Objective(s)

Deliverable(s)

Impact

  • 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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