Dear colleagues, Certara is pleased to announce the release of pyDarwin, version 1.0. pyDarwin is a machine learning solution for NONMEM model selection. This is an open source package, released under GNU GENERAL PUBLIC LICENSE. The interface is general, any combination of options (compartments, between subject variability, residual variability, between occasion variability, covariates, different absorption models, different pharmacodynamic models, different number of ODEs, nonlinear processes etc) can be searched for the optimal combination. In addition, user defined R or python code can be run after each NONMEM model allowing user defined penalties, such as PPC to be included in the search criteria. pyDarwin is an all python solution, supported on Windows, Linux and Sun Grid engine. The source package can be downloaded from https://github.com/certara/pyDarwin and the documentation can be found here: https://certara.github.io/pyDarwin/html/index.html<https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcertara.github.io%2FpyDarwin%2Fhtml%2Findex.html&data=05%7C01%7Cmark.sale%40certara.com%7C31a3289a45dc487bd7cc08da7637b77b%7C7287abd30220456e98514352bae208c9%7C1%7C0%7C637952278937389398%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Ex3%2BetN5WUFPhlmGouAB5SojE4WlEUGXJJFcc49sDM0%3D&reserved=0>
Feel free to contact me with any questions. Mark This work was supported by FDA/NIH grant (U01FD007355) (Development of a model selection method for population pharmacokinetics analysis by deep-learning based reinforcement learning (RFA-FD-21-027)). Views expressed in this announcement do not represent FDA's views or policy. Rob Bies lab at the University at Buffalo is a collaborator on this work and a co-investigator for this work. His laboratory has contributed sample datasets and suggestions on the strategies for model search Mark Sale M.D. Vice President Integrated Drug Development mark.s...@certara.com Remote-Forestville CA Office Hours 9 AM - 5 PM Eastern Time +1 302-516-1684 www.certara.com [Certara Logo] From: owner-nmus...@globomaxnm.com <owner-nmus...@globomaxnm.com> On Behalf Of Rebecca Baillie Sent: Wednesday, August 10, 2022 10:14 AM To: nmusers@globomaxnm.com Subject: [NMusers] Webinar: Injecting Reality into The Commercial Due Diligence Process for In-Licensing, Partnering, or Purchasing Pharmaceutical Assets in Development. CAUTION: This email originated from outside of Certara. Do not click links or open attachments unless you recognize the sender and know the content is safe. Injecting Reality into The Commercial Due Diligence Process for In-Licensing, Partnering, or Purchasing Pharmaceutical Assets in Development. Bill Brastow, Ph.D., CTO, Market Modeling, Rosa & Co LLC, San Carlos, CA Wednesday, August 17, 2022, 9:00 to 10:00 am PDT Register for free at https://www.rosaandco.com/webinars Abstract: When performing due diligence for in-licensing, partnering, or purchasing pharmaceutical assets in development, pharmaceutical and biotech companies evaluate the asset based on factors including the scientific data available, intellectual property of the asset, clinical development plan, competitive analysis of the commercial opportunity for the asset and a financial analysis related to revenue projections. Companies may attempt to complete this effort on their own or they may choose to use outside consulting firms to assist with components of the due diligence process. This webinar will focus on how pharmaceutical and biotech companies can inject reality into the commercial opportunity analysis by measuring expected physician demand for the drug to inform revenue projections and decisions about in-licensing, partnering, or purchasing these assets. This message (including any attachments) may contain confidential, proprietary, privileged and/or private information. The information is intended to be for the use of the individual or entity designated above. If you are not the intended recipient of this message, please notify the sender immediately, and delete the message and any attachments. Any disclosure, reproduction, distribution or other use of this message or any attachments by an individual or entity other than the intended recipient is prohibited.
