PharmML opens new opportunities for drug discovery research
A novel format for exchanging computational models in pharmaceutical R&D, PharmML (Pharmacometrics Markup Language), opens new opportunities for collaborations in drug discovery research.
About the study:
- PharmML is a key component of DDMoRe’s platform for interoperability between computational models in pharmacometric and quantitative systems pharmacology;
- PharmML encoded models can be deposited in the DDMoRe model repository, helping researchers collaborate on models to improve the design of cost effective, reliable clinical trials of new and repurposed drugs;
- A paper published in journal CPT:PSP highlights features that facilitate smooth, error-free transmission of models between tools, and that make reporting and bug tracking easier.
For predictive medicine to become a practical reality, scientists must be able to build, share and access accurate, efficient models of disease and drug action. Pharmacometric modelling is essential for designing cost–effective, reliable clinical trials to test new or repurposed medicines, but until now it has been difficult for researchers to pool their knowledge and develop these models collaboratively between organisations.
A paper in Clinical Pharmacology & Therapeutics: Pharmacometrics and Systems Pharmacology (CPT:PSP) introduces PharmML as a key component of a software platform built by the Drug Disease Model Resources consortium (DDMoRe): an Innovative Medicines Initiative to improve computational tools for drug discovery.
“PharmML is an exchange format for pharmacometric and systems-pharmacology models,” explains Lutz Harnisch, Coordinator of the DDMoRe consortium. “The public repository built on PharmML lets researchers in systems biology, quantitative systems pharmacology and pharmacometrics carefully scrutinise a broad range of published models. It provides easy access to models in their context of use, and helps authors enhance their credibility based on the use and reusability of their approaches. These are all vital to improving transparency in scientific communication.”
Launched by EMBL-EBI alumni and Babraham Institute Senior Group Leader, Nicolas Le Novère, PharmML is being developed to facilitate smooth, error-free transmission of models between tools, and to make reporting and bug tracking easier. PharmML provides support for the implementation of non-linear mixed effect models (NLME) for the analysis of longitudinal population data from clinical trials in a tool ‘agnostic’ manner. PharmML also makes it easier to navigate complex workflows and improves interactions with regulatory agencies regarding modelling and simulation.
“The development of PharmML is a brilliant example of what can be achieved when public bioscience research joins forces with pharmaceutical research, and I have no doubt that it will have a significant impact on pharmacometrics,” says Nicolas. “Standards for pharmacometric modelling developed by the DDMoRe project improve sharing and reproducibility of quantitative studies in drug development. One can use the same mathematical model with different tools and pass the model through different stages of the drug development pipeline – from preclinical to clinical. The result is that these models can be accessible to everyone by way of public model repositories.”
“The Pharmaceutical industry and regulatory agencies have a long track record of adopting standards because this makes it much easier to achieve real advances in quality, quantity and efficiency,” says Peter Milligan, Head of Pharmacometrics at Pfizer and EFPIA group participant for DDMoRe. “I see the potential for PharmML to be the standard that makes it possible to use a burgeoning variety of quantitative approaches in this sector. Until now, this has been inconceivable simply because of the inherent incompatibility of current modelling tools.”
“Designing PharmML has been a fascinating challenge, and not just a technical one,” says Maciej Swat, lead developer of PharmML at EMBL-EBI. “It requires an intimate understanding of both statistical methods used in pharmacometrics, and the needs of the modellers. We’ve been lucky to have so many top European pharmacometric groups and experts in the DDMoRe consortium, sharing their invaluable experience and know-how.”
Drug discovery and collaboration. Image: opensource.com under a Creative Commons license
Swat MJ, et al. (2015) Pharmacometrics Markup Language (PharmML): Opening new perspectives for model exchange in drug development. CPT: Pharmacometrics & Systems Pharmacology (in press). Published online 29 May
Nicolas Le Novère, group leader, Signalling programme