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Conference Details - Agenda

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2018 MIT AI in Life Sciences and Healthcare Conference

December 4-5, 2018
Day 01 | Day 02 All
 

Day 2: Wednesday, December 5th, 2018

8:30 - 9:00

Registration with Light Breakfast

Session 5: Discovery and Development

9:00 - 9:30

The Roles of AI in Healthcare
What are the prospects for applying AI to improve healthcare? Three types of problems that AI can address in healthcare will be outlined, the most challenging of which is the development of new therapeutics. To address this challenge, we leverage recent advances in machine learning and high-throughput experimentation to apply the engineering cycle to drug discovery. The engineering cycle is based on iteratively measuring a system, modeling it computationally, and manipulating it. Each time the cycle is completed, the results improve. This iterative approach is fundamental to all engineering design but, until now, has had limited impact on drug discovery. Progress on unpublished projects relating to these efforts will be described, including a collaborative, multi-institutional project called Answer ALS.
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9:30 - 10:00

From Genomics to Therapeutics: Dissection and Manipulation of Human Disease Circuitry at Single-Cell Resolution
Perhaps the greatest surprise of human genome-wide association studies (GWAS) is that 90% of disease-associated regions do not affect proteins directly, but instead lie in non-coding regions with putative gene-regulatory roles. To address this challenge, we generate transcriptional and epigenomic maps of cellular circuitry and use the resulting datasets to infer regulatory networks linking genetic variants to their target genes, their upstream regulators, the cell types where they act, and the pathways they perturb. We combine single-cell profiles, tissue-level variation, and genetic variation across healthy and diseased individuals to deconvolve bulk profiles into single-cell profiles, to recognize changes in cell type proportion associated with disease and aging, and to partition genetic effects into the individual cell types where they act. These methods are expanded to electronic health records to recognize meta-phenotypes associated with combinations of clinical notes, prescriptions, lab tests, and billing codes, to impute missing phenotypes in sparse medical records, and to recognize the molecular pathways underlying complex meta-phenotypes. Lastly, we develop programmable and modular technologies for manipulating these pathways, demonstrating tissue-autonomous therapeutic avenues in Alzheimer’s, obesity, and cancer. These results provide a roadmap for translating genetic findings into mechanistic insights and ultimately new therapeutic avenues for complex disease and cancer.
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10:00 - 10:30

Interpretable AI
This talk introduces a new generation of machine learning methods that provide state of the art performance and are very interpretable, introducing optimal classification (OCT) and regression (ORT) trees for prediction and prescription with and without hyperplanes. This talk shows that (a) Trees are very interpretable, (b) They can be calculated in large scale in practical times, and (c) In a large collection of real world data sets, they give comparable or better performance than random forests or boosted trees. Their prescriptive counterparts have a significant edge on interpretability and comparable or better performance than causal forests. Finally, we show that optimal trees with hyperplanes have at least as much modeling power as (feedforward, convolutional, and recurrent) neural networks and comparable performance in a variety of real world data sets. These results suggest that optimal trees are interpretable, practical to compute in large scale, and provide state of the art performance compared to black box methods.
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10:30 - 11:10

Networking Break

11:10 - 11:50

Identifying and Rationally Modulating Cellular Drivers of Enhanced Immunity
Immune homeostasis requires constant collaboration between a diverse and dynamic set of cell types. Within our immune tissues, distinct cellular subsets must work together to defend against pathogenic threats, maintain tolerance, and establish memory. While surveying multiple healthy individuals enables exploration of potential ensemble immune solutions, contrasts against outliers of health and disease can reveal deviations that underscore diagnostic, therapeutic, and prophylactic features of enhanced function or dysfunction. Here, I will discuss how we can leverage single-cell genomic approaches – and, in particular, single-cell RNA-Seq – to explore the extensive functional diversity among immune cells within and across individuals, and uncover, from the bottom-up, distinct cell types and states associated with improved immunity. Moreover, I will discuss emerging experimental and computational strategies for altering ensemble cellular responses through targeted intra- or extracellular induction of these preferred types and states.
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Session 6: Startup Exchange

MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.
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11:50 - 12:20

Startups Lightning Talks Part I
- BioBright, Charles Fracchia, Founder and CEO
- Catalia Health, Cory Kidd, CEO and Founder
- Engine Biosciences, Stephen Harrison, SVP and Chief Scientific Officer
- Interpretable AI, Daisy Zhuo, Cofounding Partner

12:20 - 12:50

Startups Lightning Talks Part II
- Legit, Matt Osman, Cofounder and CEO
- LuminDx, Susan Conover, Cofounder and CEO
- PathAI, Aditya Khosla, Cofounder and CTO
- ReviveMed, Leila Pirhaji, Founder and CEO
- TwoXAR, Andrew M. Radin, Cofounder and Chief Marketing Officer

12:50 - 1:50

Buffet Lunch with Startup Exhibit

1:50

Adjournment