2024 - Accelerating Clinical Translation of Antibody-Drug Conjugates with Hybrid AI
Date2024-05-30
Deadline2024-05-30
VenueONLINE-VIRTUAL, USA - United States
KeywordsLife Sciences; Clinical Trials; Drug Discovery & Development
Topics/Call fo Papers
Bringing a new drug to market costs far too much and takes far too long — and for cancer treatments especially, there is inherent urgency around getting these life-saving medications to patients faster. Antibody-drug conjugates show tremendous promise as a more selective therapy modality. But, as the industry investigates more conjugates and payload combinations, the expansion of preclinical research and experimentation is exploding.
Can adding artificial intelligence (AI) to the drug discovery and development process help manage the combinatory scale challenge posed by antibody-drug conjugates? Are all AI approaches the same? What challenges will teams face and how can they be overcome when adopting different AI approaches to their research and development plans? What can drug developers realistically expect in terms of worthwhile outcomes?
In this webinar, the expert speakers will discuss how VeriSIM Life and Debiopharm partnered to scalably investigate first-in-human (FIH) dosing strategies for antibody-drug conjugates to reduce tumor burden safely and effectively. Topics explored will include:
How AI tangibly impacts preclinical research, specifically for the development of antibody-drug conjugate therapies in this instance
What benefits of an in vivo experimentation strategy can be realized by bringing in AI
Challenges faced when trying to integrate many complex insights such as drug exposure, in vivo efficacy, toxicity thresholds and more
How to develop a systematic approach to integrate these insights in dose selection for humans
The speakers will also share details right from the first step of evaluating a technology partner to the implementation of the solution and the results.
Register for this webinar to discover the transformative role of AI in accelerating antibody-drug conjugate development for cancer treatment.
Keywords: Drug Development, Antibody, Drug Discovery, Biologics, Clinical Research, Oncology, Automation, Cancer Trials, First-in-Human, AI, Antibody-Drug Conjugate, Pre-Clinical
Can adding artificial intelligence (AI) to the drug discovery and development process help manage the combinatory scale challenge posed by antibody-drug conjugates? Are all AI approaches the same? What challenges will teams face and how can they be overcome when adopting different AI approaches to their research and development plans? What can drug developers realistically expect in terms of worthwhile outcomes?
In this webinar, the expert speakers will discuss how VeriSIM Life and Debiopharm partnered to scalably investigate first-in-human (FIH) dosing strategies for antibody-drug conjugates to reduce tumor burden safely and effectively. Topics explored will include:
How AI tangibly impacts preclinical research, specifically for the development of antibody-drug conjugate therapies in this instance
What benefits of an in vivo experimentation strategy can be realized by bringing in AI
Challenges faced when trying to integrate many complex insights such as drug exposure, in vivo efficacy, toxicity thresholds and more
How to develop a systematic approach to integrate these insights in dose selection for humans
The speakers will also share details right from the first step of evaluating a technology partner to the implementation of the solution and the results.
Register for this webinar to discover the transformative role of AI in accelerating antibody-drug conjugate development for cancer treatment.
Keywords: Drug Development, Antibody, Drug Discovery, Biologics, Clinical Research, Oncology, Automation, Cancer Trials, First-in-Human, AI, Antibody-Drug Conjugate, Pre-Clinical
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Last modified: 2024-05-16 02:49:12