Estimating human ADME properties, pharmacokinetic parameters and likely clinical dose in drug discovery

ABSTRACT

Introduction: Prediction of human absorption, distribution, metabolism, and excretion (ADME) properties, therapeutic dose and exposure has become an integral part of compound optimization in discovery. Incorporation of drug metabolism and pharmacokinetics into discovery projects has largely tempered historical drug failure due to sub-optimal ADME. In the current era, inadequate safety and efficacy are leading culprits for attrition; both of which are dependent upon drug exposure. Therefore, prediction of human pharmacokinetics (PK) and dose are core components of de-risking strategies in discovery.

Areas covered: The authors provide an overview of human dose prediction methods and present a toolbox of PK parameter prediction models with a proposed framework for a consensus approach valid throughout the discovery value chain. Mechanistic considerations and indicators for their application are discussed which may impact the dose prediction approach. Examples are provided to illustrate how implementation of the proposed strategy throughout discovery can assist project progression.

Expert opinion: Anticipation of human ADME, therapeutic dose and exposure must be deliberated throughout drug discovery from virtual/initial synthesis where key properties are considered and similar molecules ranked, into development where advanced compounds can be subject to prediction with greater mechanistic understanding and data-driven model selection.

KEYWORDS:

• Pharmacokinetics
• in vitro-in vivo extrapolation
• clearance
• steady-state volume of distribution
• absorption
• bioavailability
• clinical dose

Article highlights

• Key parameters required to predict a clinically relevant oral dose are absorption (rate and extent), clearance, volume of distribution and target efficacious exposure

• The judicious combination of these within a multi-parameter optimization tool can facilitate project telemetry

• Clearance is the single most important parameter to optimize and predict successfully, as well as arguably being the most difficult to project in human with a high degree of confidence

• C_ss,av model for dose prediction is a valid, pragmatic approach for early discovery given the minimal parameter burden. It should be considered for early ranking to make preliminary assessment within a compound series and identify areas for optimization

• Maintaining unbound exposure above target efficacious concentration for the entire dosing interval is a cautious approach to dose prediction and has the greatest parameter burden and sensitivity

• Mechanistic understanding is important in refining the prediction of human PK parameters and likely clinical dose with increased certainty for lead compounds when using advanced models

• Consideration of human ADME properties and likely therapeutic dose remains a key goal for discovery projects, and should evolve in complexity from early in the discovery phase through to first time in man

This box summarizes key points contained in the article.

Declaration of interest

P Barton is the Vice President of Drug Metabolism and Pharmacokinetics and RJ Riley the Executive Vice President of Drug Metabolism and Pharmacokinetics at Evotec. JL Sproston and AJ Lucas are also employees of Evotec. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer Disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This manuscript was funded by Evotec.