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AI in Drug Discovery Briefing

June 8 @ 8:30 am - 11:00 am

AI in Drug Discovery: A Virtual Briefing

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During this special session, we’ll consider the use of artificial intelligence in drug discovery in rare diseases, clinical studies, phenotypic drug discovery, digital biomarkers and more.

 


AI-powered, Patient-inspired Treatments for Rare Diseases
Simone Manso
Head, Neurofibromatosis Therapy Development, Healx

There are 7,000 rare diseases, affecting over 400 million people around the globe – but only 5% of those conditions have an approved treatment. Since being founded in 2014, Healx has developed the world’s most detailed biomedical knowledge graph for rare diseases, a suite of state-of-the-art AI methods, and partnerships with academics, biotechs and patient groups around the world, to identify and progress novel rare disease treatments at scale. This approach has already shown success for conditions like Fragile X syndrome. Join Simone Manso, Head of Neurofibromatosis Therapy Development at Healx, to find out more.

Augmented Intelligence in Drug Redevelopment
Friso Postma, Ph.D.
Senior Director & Head of Neurological Rare Diseases, BioXcel Therapeutics

At BioXcel Therapeutics, AI is used throughout the entire value chain to identify and develop compounds with known clinical safety for novel indications. This approach allows for rapid development of solutions for neuro-rare and neuropsychiatric disorders. Approaches and considerations are discussed for selecting “concepts”: testable hypotheses for existing compounds in new indications and how to progress concepts through the preclinical and clinical pipeline. Lastly, the identification and development of an investigational proprietary, orally dissolving thin film formulation of dexmedetomidine (BXCL501) will be discussed as well as its potential for acute treatment of agitation associated to schizophrenia and bipolar disease (New Drug Application submitted to US FDA).

AI-Driven Phenotypic Drug Discovery Delivers First-in-Class, Clinically Effective Neuropsychiatric Treatments
Emer Leahy, Ph.D. 
CEO & President, PsychoGenics

PsychoGenics has developed a target agnostic platform known as SmartCube® that has led to the discovery of numerous putative treatments for neuropsychiatric disorders including SEP-363856, a novel compound with breakthrough therapy designation, in Phase 3 clinical trials for the treatment of schizophrenia, discovered in partnership with Sunovion. SmartCube® is an automated, high-throughput testing platform that presents a sequence of challenges to a mouse through its customized hardware and extracts complex behavioral and physiological measures, in an unbiased way, using computer vision and AI. The SmartCube® platform industrializes in vivo phenotypic drug discovery by screening compound libraries in a manner that is agnostic to mechanism, thus often resulting in novel pharmacologies such as SEP-363856. In a recent Phase 2 study designed, conducted and supported by Sunovion, SEP-363856 shows robust effects across a broad range of disabling symptoms of schizophrenia, including negative symptoms, with a safety profile similar to placebo. The presentation will describe the SmartCube platform and approach to drug discovery, which offers a unique approach to neuropsychiatric drug discovery

Developing Algorithms for Digital Biomarkers
Lara Mangravite, Ph.D.
President, SAGE Bionetworks

Advances in remote data collection technologies have enabled new opportunities to develop digital biomarkers to advance disease prevention and treatment. Digital biomarkers can provide remote detection of known clinical biomarkers (e.g., home glucose monitoring), they can provide new approaches to measure traits with known clinical action (e.g., gait monitoring for fall detection), and they can be used to identify new measures for complex traits (e.g., voice recordings as a measure of cognition). In particular, they provide the opportunity to quantify outcomes of particular importance to patients such as proficiencies in activities of daily living. Here we will discuss some of the considerations that influence accurate development of digital biomarkers.

Application of Multimodal Data Analytics for Biomarker Discovery and Adaptive Clinical Trials
Magali Haas, M.D., Ph.D.
CEO & President, Cohen Veterans Bioscience

Many neuro-psychiatric conditions are diagnosed and treated based on their syndromic classification, a behavioral readout of their condition. Our programs focus on establishing a biologically-driven nosology of disease using unsupervised and other machine-learning approaches on deep multi-modal phenotypic data such as genetic, proteomic, imaging and sensor data to classify patients on the basis of biotype. This approach can then be used to stratify individuals, based on common biological mechanisms, within clinical trials, including adaptive study designs, to support a targeted treatment paradigm in future programs. This webinar will provide a lay-person’s explanation of these approaches and how they can be incorporated

Unbiased and Non-Statistical Biomarker Discovery with a new AI Training Method
Susan Kaplan
Executive Vice President & Chief Marketing Officer, Modal Technology Corp.

Modal Technology Corporation is introducing disruptive AI technology to advance biomarker research in an unbiased and non-statistical manner. As the health science industry moves forward on its path to precision medicine, drug therapy research and commercialization, the accumulation of data continues to grow as does the complexity of processing data and validating results. Modal approaches these problems in a new and unique way that reduces human bias by explaining training outcomes with a rank ordering of biomarkers produced by a deterministic process that does not rely on statistical probabilities. This discussion will provide a layman’s overview of these new capabilities and how they were applied to a medical use case that allowed researchers to identify and stratify the biomarkers related to their project, leading to modifications in the standard of patient care and significant optimizations of their research process by reducing time, cost and the amount of effort required by data analysts.

Q&A Moderated by:
Daniela Brunner, Ph.D.
Chief Innovation Officer, PsychoGenics


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Details

Date:
June 8
Time:
8:30 am - 11:00 am
Event Category: