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2026 年 3 月 3 日

In early drug discovery, teams often need to make critical decisions with limited data. Physiologically-based pharmacokinetic (PBPK) modeling integrates human physiology with compound-specific properties in a mechanistic framework to predict drug exposure, supporting key discovery and translational applications such as:

  • Compound selection
  • First-in-human (FIH)
  • PK prediction
  • Early drug-drug interaction (DDI) screening
  • Early formulation decisions

Simcyp® Discovery is an intuitive PBPK software for small molecule drug discovery and development, derived from the industry-leading Simcyp Simulator, to support confident pre-IND decision-making. Here, we explore how Simcyp Discovery accelerates early drug development.

What is Simcyp and how does it help in drug discovery?

Simcyp is a PBPK modeling software suite that supports drug development across the lifecycle, with three flagship products: Simcyp Simulator, Simcyp Discovery, and Simcyp Biopharmaceutics. Simcyp Discovery is tailored for small molecule discovery and translational scientists.

Compared to other drug discovery tools, Simcyp provides a continuous PBPK workflow across drug discovery and development. Early investment in PBPK modeling through Simcyp Discovery enables model reusability and scalability across development milestones.

Integrating PBPK modeling in drug discovery enables teams to:

  • Integrate all available discovery data (in vitro, early in vivo, and physicochemical properties) into a single mechanistic framework, even when data is sparse.
  • Translate in vitro findings to in vivo prediction more confidently, potentially reducing the need for extensive animal experiments across multiple species.
  • Capture multiphasic PK profiles, explore nonlinear absorption or clearance, and test hypotheses.
  • Run rapid “what-if” simulations that reduce uncertainty and support informed compound prioritization and development planning.

Simcyp Discovery’s key areas of application include:

  • Compound triage and pipeline optimization: PBPK simulations translate target product profile requirements into clear laboratory objectives to support compound prioritization.
  • First-in-human (FIH) PK prediction: A learn-confirm cycle helps build confidence in exposure predictions while minimizing reliance on multiple animal species where possible.
  • Early drug-drug interaction (DDI) screening: Simcyp Discovery includes tools for early precipitant and object risk assessment using static approaches aligned with regulatory expectations.
  • Early formulation assessment: Oral exposure can be limited by solubility, particle size, dissolution rate, or permeability. Simcyp Discovery supports sensitivity-based exploration of these drivers, enabling earlier formation and development decisions.

What are the main features of Simcyp Discovery?

Simcyp Discovery includes prebuilt PBPK model frameworks for mouse, rat, dog, and monkey, as well as a healthy volunteer human population, enabling efficient iteration across species during model development.

Supporting IV and oral dosing, Simcyp Discovery allows teams to explore both single- and multiple-dose scenarios and evaluate plasma and tissue concentration-time profiles in virtual individuals or populations.

Simcyp Discovery Version 2 introduced several updates designed to accelerate model development and improve usability, including:

  • Dose finding tool to support selection of doses that achieve predefined PK or PD targets in a given species or population
  • Structure-based predictors to estimate key physicochemical properties directly from chemical structure, supporting earlier PBPK model development when experimental data are limited
  • Expanded annotation and traceability to document parameter sources and modeling assumptions
  • Workflow automation for batch workspace generation, scenario executions, and efficient parameter exploration
  • Interactive output comparison tools to rapidly assess differences across outcomes of simulations.
  • Simcyp Cloud to reduce local computational burden and accelerate simulation turnaround.
  • ‘Ask Simcyp’, a ChatGPT based chat exclusively trained on Simcyp Discovery help materials that supports users when it is needed the most.

Static DDI tool: early screening aligned with evolving guidance

Simcyp Discovery includes a static DDI prediction tool designed for early-stage evaluation using basic cut-off and mechanistic static approaches. Results are compared against regulatory evaluation criteria to support structured interpretation and identify when further investigation may be needed.

This capability is increasingly important as global regions align under the ICH M12 Drug Interaction Studies guideline, providing a harmonized framework for enzyme-and transporter-mediated DDI assessment.

Learn more Simcyp Discovery

Simcyp Discovery helps in drug discovery include first-in-human dose prediction, compound triage and pipeline optimization, early drug-drug interaction screening, and early formulation assessment.

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Authors

Claire Ciana, PhD

Senior Research Scientist

With a PhD and a Postdoc in organic chemistry, she gained experience in drug discovery, working as medicinal chemist at Actelion (biopharmaceutical company, Switzerland) and Sygnature Discovery (CRO, UK). After several years, she transferred to the DMPK department where she specialised on metabolite identification and reactive metabolites screening. She joined the Translational Science in DMPK team at Certara Predictive Technologies in January 2022.

Aki Heikkinen, PhD

Principal Scientist

Aki T. Heikkinen is a Principal Scientist at Certara Predictive Technologies. After qualifying as a pharmacist in 2005 Aki received his PhD from the University of Eastern Finland, Kuopio, Finland, in 2010 for his thesis on efflux transporter and permeation kinetics in vitro. Following this he worked for 4 years on intestinal absorption modeling and in vitro to in vivo extrapolation of intestinal and hepatic metabolism in human and dog as a Roche Postdoctoral Research Associate both at the F. Hoffman – La Roche site in Basel, Switzerland, and at the University or Eastern Finland.

Before joining Certara Predictive Technologies in October 2022, Aki worked for 8 years at Admescope, Oulu, Finland, where he was responsible of services and internal R&D on drug drug interactions, transporters, permeation and PBPK modeling.

At CPT Aki is currently working on development of compound files, modeling of transporter biomarkers, and development of the Simcyp Discovery simulator.

This blog was originally published in July 2022 and has been updated for accuracy and comprehensiveness.

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