AI and machine learning in drug development and delivery are revolutionizing the pharmaceutical industry by enhancing both the speed and accuracy of drug discovery and patient treatment. In drug development, AI algorithms analyze vast datasets to identify potential drug targets, predict compound effectiveness, and optimize clinical trial designs. Machine learning models can predict the pharmacokinetics and toxicity of molecules, helping to reduce development costs and time. When applied to drug delivery, AI and machine learning enable the creation of personalized therapies, tailoring drug treatments based on genetic profiles and disease characteristics. These technologies also optimize drug formulations, improving bioavailability and ensuring precise targeting of drugs to specific organs or tissues. AI and Machine Learning in Drug Development and Delivery are driving innovations that streamline the process, reduce risks, and provide more effective, personalized treatments for patients.
Consolato M Sergi
Universities of Alberta and Ottawa, Canada
Vladlen Slepak
University of Miami Miller School of Medicine, United States
Andreas M Papas
Antares Health Products, United States
Sergey Suchkov
The Russian University of Medicine and Russian Academy of Natural Science-Moscow, Russian FederationSubmit your abstract Today
Title : Medical liver biopsy: Toward a personalized approach
Consolato M Sergi, Universities of Alberta and Ottawa, Canada
Title : Ectopically expressed olfactory receptors as an untapped family of drug targets and discovery of agonists and antagonists of OR51E1, an understudied G Protein-Coupled Receptor
Vladlen Slepak, University of Miami Miller School of Medicine, United States
Title : Mathematical modeling the disc diffusion test: Antibacterial activity of copper-doped SnO2
Paulo Cesar De Morais, Catholic University of Brasilia, Brazil
Title : Emerging formulation and delivery applications of Vitamin E TPGS
Andreas M Papas, Antares Health Products, United States
Title : Personalized and Precision Medicine (PPM) as a unique healthcare model through design-inspired biotech- & biopharma-driven applications and upgraded business marketing to secure the human healthcare and biosafety
Sergey Suchkov, The Russian University of Medicine and Russian Academy of Natural Science-Moscow, Russian Federation
Title : Design and evaluation of exo-itc: A bilayer fibrous system for controlled exosome delivery in dermatological applications
Luis Jesus Villarreal Gomez, FCITEC - Universidad Autónoma de Baja California, Mexico
Title : Macitentan/Tadalafil Combination– An additional value in pharmacotherapy of pulmonary arterial hypertension
Miroslav Radenkovic, University of Belgrade, Serbia
Title : Understanding drug transport in plasma: The role of protein binding
Saad Tayyab, UCSI University, Malaysia
Title : Drug development - Importance, trends and digital transformation
Gurpreet Singh, IQVIA, United Kingdom
Title : Navigating the regulatory landscape for nanotechnology-based pharmaceuticals: challenges and strategies for harmonization
Srividya Narayanan, Northeastern University, United States