In Silico DMPK Modeling Discussion Group

The In Silico DMPK expert is an emerging position for which there is no formal training program available. Generally In Silico DMPK experts are either Computational Chemists learning about DMPK sciences or DMPK Scientist acquiring a computational background. The strategic position of this role requires synergistic collaboration with medicinal chemists, computational chemists and DMPK scientists.

We have initiated an IQ cross-industry discussion group aiming to fill the knowledge gap in field, to share strategies and to define best practices for In Silico DMPK scientists to influence decision-making in projects.


Anticipated value for the creation of this group:

Define best practices for established computational tools

Define best strategies for less explored/validated specific problems

Share strategies to timely influence decision making in projects

Share strategies to make chemistry more accessible to DMPK Reps

Share strategies to improve IVIV and/or ISIV correlations

Identify strategies/practices to improve in vitro ADME data management and/or analysis

Identify opportunities for cross-company collaboration on specific platforms (e.g., match-pair analysis)


Tasks that maybe associated with the role of In Silico DMPK experts are:

Creating global or local predictive models for routinely screened properties

Use structure based modeling to study the interaction of small molecules with enzymes such as metabolizing enzymes or nuclear receptors

Mine in vitro data to predict the in vivo behavior of small molecules in the PK world (e.g. IVIV correlation) or in the PD world (e.g. metabolomics)

Provide frameworks for IVIV and cross-species data analysis

Expedite or facilitate data analysis, circulation and/or management

Provide a framework to facilitate multi-parameter optimization


In our view, the role of the In Silico DMPK expert is aimed to:

Provide fit for purpose solutions to novel and/or recurring problems

Enhance the ability of DMPK scientists to influence chemistry and chemists to incorporate DMPK knowledge in multi-objective optimization

Bring DMPK Reps closer to the chemistry world, increasing their impact before candidate selection stage


Typical challenges associated with this role are:

Identification of best practices (too many “story of success” in literature)

Fit in the drug design loop; it is challenging for scientists outside projects to become aware of problems and provide solutions before the MedChem lead opts for less “hypothesis driven” strategies (e.g. extensive SAR)

Perception problem; well validated computational tools can sometimes be questioned without real evidence; rules of thumb are often preferred. This is linked to the interpretability issue but also to the unperceived risk of restricting the chemical space explored