Transfer learning empowers accurate pharmacokinetics prediction of small samples
This study explores the fundamentals, classifications, toolkits and applications of various transfer learning techniques for PK prediction, demonstrating their utility through three practical case studies. This work will serve as a reference for drug design researchers. Teaser: Explore how transfer learning revolutionizes pharmacokinetic prediction, overcoming data scarcity with innovative machine learning techniques. Discover its classifications, applications and practical case studies in drug design.PMID:38460571 | DOI:10.1016/j.drudis.2024.103946 (Source: Drug Discovery Today)
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Wenbo Guo Yawen Dong Ge-Fei Hao Source Type: research
Master protocols and other innovative trial designs in inflammation and immunology to expedite clinical drug development
Drug Discov Today. 2024 Mar 7:103948. doi: 10.1016/j.drudis.2024.103948. Online ahead of print.ABSTRACTMaster protocol designs such as umbrella and basket studies allow multiple compounds or multiple target populations to be evaluated simultaneously within a single protocol, and THEY have been widely adopted in oncology clinical trials. These novel designs can also be applied in other therapeutic areas, where they could have several benefits over conducting traditional randomized controlled trials. Here, we detail Pfizer's recent implementations of master protocol designs in inflammation and immunology clinical studies, fo...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Elena Peeva Anindita Banerjee Christopher Banfield Koshika Soma Jared Christensen Sandeep Menon Michael S Vincent Mikael Dolsten Source Type: research
Augmenting DMTA using predictive AI modelling at AstraZeneca
Drug Discov Today. 2024 Mar 7:103945. doi: 10.1016/j.drudis.2024.103945. Online ahead of print.ABSTRACTDesign-Make-Test-Analyse (DMTA) is the discovery cycle through which molecules are designed, synthesised, and assayed to produce data that in turn are analysed to inform the next iteration. The process is repeated until viable drug candidates are identified, often requiring many cycles before reaching a sweet spot. The advent of artificial intelligence (AI) and cloud computing presents an opportunity to innovate drug discovery to reduce the number of cycles needed to yield a candidate. Here, we present the Predictive Insi...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Gian Marco Emma Evertsson David J Riley Christian Tyrchan Prakash Chandra Rathi Source Type: research
Transitioning biomedical research toward human-centric methodologies: systems-based strategies
This article advocates systemic thinking, endorsed by the OECD and the EU, offering policymakers a new framework for effective strategies to unlock the potential of human-centric methods.PMID:38460569 | DOI:10.1016/j.drudis.2024.103947 (Source: Drug Discovery Today)
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Helder Constantino Francesca Pistollato Troy Seidle Source Type: research
Rise of the Allotrope Simple Model: update from 2023 Fall Allotrope Connect
Drug Discov Today. 2024 Mar 7:103944. doi: 10.1016/j.drudis.2024.103944. Online ahead of print.ABSTRACTThe Allotrope Foundation (AF) started as a group of pharmaceutical companies, instrument, and software vendors that set out to simplify the exchange of data in the laboratory. After a decade of work, they released products that have found adoption in various companies. Most recently, the Allotrope Simple Model (ASM) was developed to speed up and widen the adoption. As a result, the Foundation has recently added chemical companies and, importantly, is reworking its business model to lower the entry barrier for smaller comp...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Christopher Haynie Spencer Gardiner Dennis Della Corte Source Type: research
Transfer learning empowers accurate pharmacokinetics prediction of small samples
This study explores the fundamentals, classifications, toolkits and applications of various transfer learning techniques for PK prediction, demonstrating their utility through three practical case studies. This work will serve as a reference for drug design researchers. Teaser: Explore how transfer learning revolutionizes pharmacokinetic prediction, overcoming data scarcity with innovative machine learning techniques. Discover its classifications, applications and practical case studies in drug design.PMID:38460571 | DOI:10.1016/j.drudis.2024.103946 (Source: Drug Discovery Today)
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Wenbo Guo Yawen Dong Ge-Fei Hao Source Type: research
Master protocols and other innovative trial designs in inflammation and immunology to expedite clinical drug development
Drug Discov Today. 2024 Mar 7:103948. doi: 10.1016/j.drudis.2024.103948. Online ahead of print.ABSTRACTMaster protocol designs such as umbrella and basket studies allow multiple compounds or multiple target populations to be evaluated simultaneously within a single protocol, and THEY have been widely adopted in oncology clinical trials. These novel designs can also be applied in other therapeutic areas, where they could have several benefits over conducting traditional randomized controlled trials. Here, we detail Pfizer's recent implementations of master protocol designs in inflammation and immunology clinical studies, fo...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Elena Peeva Anindita Banerjee Christopher Banfield Koshika Soma Jared Christensen Sandeep Menon Michael S Vincent Mikael Dolsten Source Type: research
Augmenting DMTA using predictive AI modelling at AstraZeneca
Drug Discov Today. 2024 Mar 7:103945. doi: 10.1016/j.drudis.2024.103945. Online ahead of print.ABSTRACTDesign-Make-Test-Analyse (DMTA) is the discovery cycle through which molecules are designed, synthesised, and assayed to produce data that in turn are analysed to inform the next iteration. The process is repeated until viable drug candidates are identified, often requiring many cycles before reaching a sweet spot. The advent of artificial intelligence (AI) and cloud computing presents an opportunity to innovate drug discovery to reduce the number of cycles needed to yield a candidate. Here, we present the Predictive Insi...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Gian Marco Emma Evertsson David J Riley Christian Tyrchan Prakash Chandra Rathi Source Type: research
Transitioning biomedical research toward human-centric methodologies: systems-based strategies
This article advocates systemic thinking, endorsed by the OECD and the EU, offering policymakers a new framework for effective strategies to unlock the potential of human-centric methods.PMID:38460569 | DOI:10.1016/j.drudis.2024.103947 (Source: Drug Discovery Today)
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Helder Constantino Francesca Pistollato Troy Seidle Source Type: research
Rise of the Allotrope Simple Model: update from 2023 Fall Allotrope Connect
Drug Discov Today. 2024 Mar 7:103944. doi: 10.1016/j.drudis.2024.103944. Online ahead of print.ABSTRACTThe Allotrope Foundation (AF) started as a group of pharmaceutical companies, instrument, and software vendors that set out to simplify the exchange of data in the laboratory. After a decade of work, they released products that have found adoption in various companies. Most recently, the Allotrope Simple Model (ASM) was developed to speed up and widen the adoption. As a result, the Foundation has recently added chemical companies and, importantly, is reworking its business model to lower the entry barrier for smaller comp...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Christopher Haynie Spencer Gardiner Dennis Della Corte Source Type: research
Transfer learning empowers accurate pharmacokinetics prediction of small samples
This study explores the fundamentals, classifications, toolkits and applications of various transfer learning techniques for PK prediction, demonstrating their utility through three practical case studies. This work will serve as a reference for drug design researchers. Teaser: Explore how transfer learning revolutionizes pharmacokinetic prediction, overcoming data scarcity with innovative machine learning techniques. Discover its classifications, applications and practical case studies in drug design.PMID:38460571 | DOI:10.1016/j.drudis.2024.103946 (Source: Drug Discovery Today)
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Wenbo Guo Yawen Dong Ge-Fei Hao Source Type: research
Master protocols and other innovative trial designs in inflammation and immunology to expedite clinical drug development
Drug Discov Today. 2024 Mar 7:103948. doi: 10.1016/j.drudis.2024.103948. Online ahead of print.ABSTRACTMaster protocol designs such as umbrella and basket studies allow multiple compounds or multiple target populations to be evaluated simultaneously within a single protocol, and THEY have been widely adopted in oncology clinical trials. These novel designs can also be applied in other therapeutic areas, where they could have several benefits over conducting traditional randomized controlled trials. Here, we detail Pfizer's recent implementations of master protocol designs in inflammation and immunology clinical studies, fo...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Elena Peeva Anindita Banerjee Christopher Banfield Koshika Soma Jared Christensen Sandeep Menon Michael S Vincent Mikael Dolsten Source Type: research
Augmenting DMTA using predictive AI modelling at AstraZeneca
Drug Discov Today. 2024 Mar 7:103945. doi: 10.1016/j.drudis.2024.103945. Online ahead of print.ABSTRACTDesign-Make-Test-Analyse (DMTA) is the discovery cycle through which molecules are designed, synthesised, and assayed to produce data that in turn are analysed to inform the next iteration. The process is repeated until viable drug candidates are identified, often requiring many cycles before reaching a sweet spot. The advent of artificial intelligence (AI) and cloud computing presents an opportunity to innovate drug discovery to reduce the number of cycles needed to yield a candidate. Here, we present the Predictive Insi...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Gian Marco Emma Evertsson David J Riley Christian Tyrchan Prakash Chandra Rathi Source Type: research
Transitioning biomedical research toward human-centric methodologies: systems-based strategies
This article advocates systemic thinking, endorsed by the OECD and the EU, offering policymakers a new framework for effective strategies to unlock the potential of human-centric methods.PMID:38460569 | DOI:10.1016/j.drudis.2024.103947 (Source: Drug Discovery Today)
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Helder Constantino Francesca Pistollato Troy Seidle Source Type: research
Rise of the Allotrope Simple Model: update from 2023 Fall Allotrope Connect
Drug Discov Today. 2024 Mar 7:103944. doi: 10.1016/j.drudis.2024.103944. Online ahead of print.ABSTRACTThe Allotrope Foundation (AF) started as a group of pharmaceutical companies, instrument, and software vendors that set out to simplify the exchange of data in the laboratory. After a decade of work, they released products that have found adoption in various companies. Most recently, the Allotrope Simple Model (ASM) was developed to speed up and widen the adoption. As a result, the Foundation has recently added chemical companies and, importantly, is reworking its business model to lower the entry barrier for smaller comp...
Source: Drug Discovery Today - March 9, 2024 Category: Drugs & Pharmacology Authors: Christopher Haynie Spencer Gardiner Dennis Della Corte Source Type: research
