effects. PK/PD pediatric studies play a key role in clinical programs and are a central contributor to define pediatric dose adjustments specified in the product labeling. The graph (Fig. 6.39) in this figure shows substantial differences in AUC for different BSA (body surface areas in meters squared) for sotalol [23].

Populations in pediatric PK/PD studies frequently cover a much wider range in body size than similar studies in adults. Therefore, appropriately applying a size adjustment approach is critical in dose selection of the trials, optimal sampling design and PK/PD modeling for other covariates, and, ultimately, in dosage regimen recommendations. Limited sampling designs are a frequently used feature in population PK/PD analysis in pediatric populations. Sufficient methodology is now available to allow for the design of Dose-optimality or random sampling based schemes and validation of these schemes. Furthermore, reliable and unbiased results can be obtained using various Bayesian and nonlinear mixed effects modeling approaches, even though the data is sparse and unbalanced. Population PK/PD models, if used as bridging to recommend dose, should be carefully validated or evaluated.

The recent regulatory initiatives and policies have stimulated pediatric clinical studies resulting in improved understanding of the PK/PD of drugs prescribed in pediatrics.

r Objectives o Used for Diagnosis oTool for staging disease c. Indicator of disease status c Predict and/or monitor clinical response to an intervention r Example c CRP & cholesterol lowering are good biomarkers for clinical outcome

AAPS Biomarker Workshop, Sept. 2005

Fig. 6.40. Biomarker Development

Reprinted with permission from American Association of Pharmaceutical Scientists. Arlington, VA.

r Formalizes the Decision Making Process o Assumptions ^ Opinions ^ Decisions o Knowledge repository of disease, patient population, drug action, and trial designs r Enhances Communication o (Clinical) Development Team o Regulatory Agencies o Senior Management

Fig. 6.41. Modeling and Simulation in Drug Development

The pursuit of relationships between systemic exposure and both response and toxicity specifically in pediatric populations represents the frontier in limited sampling design, population PK/PD modeling, and dose optimization. The integration of model-based techniques as a tool in these investigations is both rational and necessary.

Biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. An example would be low-density cholesterol (LDL) and CRP (C-reactive protein) for heart disease, as represented in Fig. 6.40, which displays death rates over time with different levels of CRP and LDL [24]. Pharmacogenomics guidance further defines possible, probable, and known valid biomarker categories depending on available scientific information on the marker. Biomarkers are used to diagnose disease and predict response to therapies. Their development often is a stepwise progression throughout the research development process. At the preclinical stage, early methods are developed in animals, including correlation of animal response data with the marker, correlation of toxic-ity to drug exposure, and developing the bioassay parameters and variables for the biomarker. In phase II stage, the proof of concept should be accomplished, with data in healthy volun teers, clinical data in patients with the target disease (e.g., predictability of biomarker to disease outcomes, subpopulations of importance), and fine tuning of the test methodology and validation of the biomarker. In phase III, biomarker evolves to become a surrogate marker, necessitating full validation (phase III data for outcomes and biomarker correlation, full test criteria), full regulatory engagement for U.S. and worldwide approvals, and labeling considerations.

Recently, there is an increasing interest on implementation of modeling and simulation (M&S) to improve the efficiency of the efficacy and safety assessment of new chemical entities and to aid decision-making in preclinical and clinical development (Fig. 6.41). The contribution of pharmacokinetics/pharmacodynamics (PK/PD) in drug development was well established in the early 1990s. Since then, the exposure-response modeling and population approach has been expanded to clinical trial simulation. Companies now have large repositories of information for diseases, MPK data, PD data, trial designs, and patient populations, which can be used in the M&S. After 10 + years of practice of this technology, the value of M&S in expediting drug development and reducing the cost has been recognized. Acceptance by regulatory authorities for M&S is now available, as long as the negotiation for an NCE is done in advance and well accepted by the FDA in the development plan. Mathematical modeling, decision analysis, and simulation are powerful approaches that can be employed to enhance critical path drug development. The modeling and simulation need concurrence of the development team and senior management on its value and need to fit into the development plan and all the study results, followed by communication with and acceptance by regulatory authorities.

The focus of MPK package in a NDA is to address the FDA's approach of question-based review. The fundamental regulatory expectations are presented in Figs. 6.42 and 6.43. What is the dose versus systemic exposure relationship for drug and its metabolites? How are the responses (efficacy and/or r What is the dose versus systemic exposure relationship for drug and its metabolites? r How are the responses (efficacy and/or adverse effects) in relation to the dose and/or plasma drug concentration? r How does exposure vary c In the presence and absence of intrinsic (age, gender, race, renal or liver function...)? o In presence and absence of extrinsic factors (food, concomitant drugs, smoking.)?

Fig. 6.42. Regulatory Expectations: Key PKPD Topics

Small Molecules: r FDA Regulatory Guidances o FIM and Exposure Response o Population PK / PD and In vitro Metabolism o BA / BE and Pediatric o In Vitro In Vivo Correlation r ICH Guidances o QTC

Biological Products: r Manufacturing process is crucial.

r Combination of several conformations (e.g., isoforms) that cannot be distinguished by standard analytical methods. r Metabolic breakdown primarily driven by breakdown of proteins. r Production of antibodies, especially neutralizing antibodies o Can affect ADME, toxicology, and efficacy of compound o Show dramatic inter-species differences; thus, identifying animal models for toxicology and even pharmacology is difficult.

Fig. 6.43. Regulatory Expectations adverse effects) in relation to the dose and/or plasma drug concentration? How does exposure vary in the presence and absence of intrinsic (age, gender, race, renal or liver function . . .) or in presence and absence of extrinsic factors (food, concomitant drugs, smoking . . .)?

For small molecules, FDA guidance primarily addresses the following six areas: FIM and exposure response, population PK/PD, in vitro metabolism, BA/BE, pediatric information, and in vitro-in vivo correlation. ICH guidances add QTC. For biological products, manufacturing process is crucial. Combination of several related conformations (e.g., isoforms) cannot be distinguished by standard analytical methods. Metabolic breakdown is primarily driven by breakdown of proteins. Production of antibodies, especially neutralizing antibodies, can affect ADME, toxicology, and efficacy of compound and show dramatic inter-species differences; thus, identifying relevant animal models for toxicology and even pharmacology is difficult [25, 26].

Drug development is a sequential process—from discovery to preclinical through phase I to phase III and beyond including PK studies as well, as displayed in this MPK summary in Fig. 6.44. PK work involves in vitro work during discovery stage, followed by preclinical development with substantial animal research, next clinical phase I in healthy normal subjects, and then phases II-III in patients with the target disease. The role of metabolism and pharmacokinetics is to address the question of which compound should be selected for development among multiple candidates and how the compound should be dosed. The strategy of developmental value chain from early discovery to late-stage development is to develop and utilize new technologies in vitro or animal models that are predictive of human absorption, distribution, metabolism, and metabolism. The integration of pharmacokinetics/pharmacodynam-ics has recently become an important component of drug development programs to understand the drug action on the


Preclinical / Toxicokinetics

Phase I

Phase I

Labeling in vitro model Animal model Healthy subjects Patients Patients PK-► Exposure



Plasma Interstitial fluid Cells

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