Versatile tool for translational modeling and simulation
It is now well-accepted that physiologically-based pharmacokinetic (PBPK) modeling and simulation is a powerful tool in drug development. PBPK helps answer a myriad of “what if” questions that cannot be addressed without lengthy and expensive clinical studies.
PBPK also has numerous applications to inform critical decisions early in the R&D process. The new Simcyp Discovery Simulator is an intuitive PBPK software that delivers confidence in decision-making during the pre-Investigational New Drug (IND) Application and translational stages. Derived from the gold-standard Simcyp Simulator, Simcyp Discovery advances and accelerates small molecule discovery and development.
Triage the best drug candidates
High-throughput screening speeds up the process of identifying promising lead compounds. Simcyp Discovery facilitates rapid batch screening of thousands of potential compounds to identify the most promising candidates.
It also helps guide decisions regarding the optimal laboratory objectives for a chemical series to achieve the target product profile (TPP).
Predict First-In-Human (FIH) PK
A first-in-human protocol is required in an IND application. In vitro in vivo extrapolation (IVIVE) – linked PBPK can be applied for PK and dose prediction in early stages where data are limited, and it enables a mechanistic understanding of the effect of physiological variables.
Simcyp Discovery uses PBPK to predict early drug development outcomes by delivering a unified interface for both animal and human simulation for translational research. It includes PBPK models for human, mouse, rat, dog and monkey. Establishing IVIVE in pre-clinical species can inform IVIVE and PBPK model building in human. Simcyp Discovery provides a range of model options – the minimal PBPK model, the full PBPK model, a compartmental model, which includes 1, 2 and 3 compartmental PK models, as well as a first order (FO) model and advanced dissolution, absorption and metabolism (ADAM) model.
To determine the required dose to achieve the desired concentration, you can conduct simulations at different dose levels and frequencies. You can also perform different sensitivity analyses using the automated sensitivity analysis tool.
Simcyp Static DDI Prediction Tool
Assessment of drug-drug interaction (DDI) liabilities is a critical safety component of any drug development program. Early predictions of harmful DDIs inform rapid decision-making.
The Simcyp Static DDI Prediction Tool quickly flags the DDI risk for enzymes and transporters based on published regulatory guidance (including the FDA, EMA, PMDA, NMPA and the draft ICHM12 guidance).
Main features include basic (cut-off) models, including competitive inhibition, mechanism-based inhibition, induction, transporter inhibition, and mechanistic static interaction models. DDI risk from both perpetrator and victim perspectives can be explored.
The Simcyp Static DDI Prediction Tool is integrated within
Simcyp Discovery and is also available as a standalone app.
Conduct early formulation screening
PBPK is increasingly being applied to formulation development by helping to guide the development of new and alternate formulations, thereby increasing the number and type of patients that can benefit from therapies.
Simcyp Discovery offers capabilities to strengthen work in early formulation screening. You can perform sensitivity analysis to determine what is needed to improve the formulation, such as increasing solubility using a spray-dried dispersion formulation or reducing particle size via micronisation.
Hannah has over 20 years experience in global pharmaceutical organizations, possessing a particularly strong background in PBPK and PKPD modelling, She has over 50 publications in PBPK/PKPD modelling and other DMPK related topics, and considerable experience influencing drug research and development programs through modelling and simulation.
Masoud leads teams of scientists and programmers on the design, development and implementation of various aspects of systems pharmacology including in vitro-in vivo extrapolation techniques, physiologically-based PK/PD models, and the application of top-down PopPK data analysis to PBPK models in healthy volunteer and patient populations.
Iain leads the science team that is responsible for further developments of the population based physiologically-based PK/PD simulators to meet the needs of Simcyp Consortium members. Prior to joining Certara, he spent 12 years working in the Pharmacokinetics, Dynamics and Metabolism Department at Pfizer Global Research & Development.