Gini Deshpande, PhD, is founder & CEO of NuMedii, a next generation biopharma company that pioneered the use of artificial intelligence and advanced data sciences to rapidly discover new precision therapeutics. As CEO, she structured critical partnerships with several large pharma companies and raised Series A from top tier VC firms. Previously, she helped Affymetrix and other companies with market development strategies for their ground-breaking technologies. She led innovation at Children’s Hospital Boston for the creation of new devices for the tiniest of patients and vaccines for the developing world. Read her full bio.

Interview with Gini Deshpande of NuMedii

Q: What need is NuMedii addressing?

A: NuMedii, has been pioneering the use of Big Data, artificial intelligence (AI) and systems biology since 2010 to accelerate the discovery of precision therapies to address high unmet medical needs. Artificial Intelligence approaches are a natural fit to harness Big Data as they provide a framework to ‘train’ computers to recognize patterns and sift through vast amounts of new and existing genomic and other biomedical data to unravel diverse complex biological networks involved in disease processes. We use multiple AI approaches, ranging from classical machine learning techniques to newer deep learning systems, to rapidly discover connections between medicines and diseases at a systems level. Our AI approaches are also being used to identify subsets of patients and therapies that are likely to modulate these complex networks for each patient subgroup. As we have worked extensively with Big Data and AI, we have developed a deep appreciation of the limitations of AI. At NuMedii, we prefer to think of AI more as “Augmented Intelligence” than “Artificial Intelligence.” We couple AI, Big Data and systems biology with human intelligence enabling our scientists to have access to more and better synthesized information than otherwise feasible. Our goal is to use this combined system of human + machine intelligence to help speed up drug discovery, cut R&D costs and decrease failure rates in clinical trials, all of which can eventually lead to better, more precise medicines.

Q: What are the products and/or services NuMedii offers/develops to address this need? What makes NuMedii unique?

A: As a next generation biopharma company, NuMedii has built a powerful technology – AIDD Technology – that harnesses Big Data and AI to rapidly discover connections between drugs and diseases at a systems level. The company has efficiently extracted information from a vast array of disparate data stores to create a structured, proprietary data resource spanning hundreds of diseases and thousands of compounds. NuMedii’s proprietary AI algorithms enable the company to extend well beyond conventional ‘target-centric’ drug discovery approaches by facilitating the exploration of favorable ‘poly-pharmacology’ profiles that can potentially improve therapeutic efficacy by modulating effects on multiple disease pathways.

Q: What is your role at NuMedii and what excites you about your work?

A: I am the founder and CEO and a molecular biologist by training with more than 17 years of experience turning cutting-edge scientific concepts into products that benefit patients. The potential for AI to significantly alter the landscape in medicine is huge, and there is a lot of excitement and interest in this space. We are seeing sizeable, established companies jumping in with large-scale investments, as well as the launch of hundreds of small startups. Part of the excitement comes from the fact that healthcare comprises a large portion of the U.S. economy, and thus is of interest to many companies, especially tech companies. Today there are AI companies that now touch each of the four key stakeholder pillars: patients (e.g., Apple), providers (e.g., Sense.ly), payers (e.g., Optum, GNS) and pharma (e.g., NuMedii, Benevolent AI, Berg).

Q: When thinking about NuMedii and the domain NuMedii is working in, what are some of the recent breakthroughs that are propelling the field forward and how will they impact healthcare?

A: Artificial Intelligence will continue to have increased impact on multiple aspects of healthcare. Over a period of time, quantum computing is projected to become more readily available, enabling new applications in both the front end of the drug discovery process and also downstream in clinical development. Once we have a few successful examples of how AI has streamlined and enabled us to expedite drug discovery, we will see broader adoption and expect that AI will be routinely used in R&D in the next five-to-ten years.

Most AI start-ups have ended up working with pharma and biotech partners in various ways to help them with their drug discovery efforts. Going forward there will continue to be several providers of AI services. But we will also see more startups become drug developers themselves – a full integration of both AI-driven drug discovery coupled with serious drug development capabilities – to speed up the process all along the way. At NuMedii, we’re certainly going down this road ourselves by developing our own pipeline – we refer to it as “eating our own caviar.” Several others like BenevolentAI, Recursion and Berg Pharma are also developing their own pipelines, and we expect to see more companies follow in our footsteps.

Q: What are the short-term challenges that NuMedii and its peers are facing?

A: Drug discovery and development are highly data-intensive processes, with disparate types of data being generated (from molecules to clinical trial encounters) and a lot of information being tracked. These processes have historically been trial-and-error ridden processes, with high failure rates and costs that are in the billions. Several factors have contributed to these problems: biology is inherently complex and disease manifestation in patients varies across the patient population. Genetic, environmental and other factors also determine how a disease will progress and how patients respond to a given therapy. Thus, these R&D processes and the variabilities involved become a Big Data problem. Artificial Intelligence, coupled with correct data, has the potential to make drug discovery and development less error prone and increase the likelihood of success both in trials and the real-world setting. The hope is that ideally, with AI, some predictability could be regained in these processes.

Compute power is certainly no longer a rate-limiting step for the use of AI in drug discovery. Effective use of AI requires large amounts of relevant, high quality and consistent data to train algorithms for accurate pattern recognition. These data can be particularly challenging to both in terms of access, as well as ensuring that the right data are used for a discovery project. Often data are kept in silos and spread across organizations. In addition, biomedical data are very diverse, spanning multiple “omics” information, such as genetic, genomic, proteomic and metabolomics, as well as environmental exposures, ranging from chemical structures to clinical information. Mapping relationships between these diverse data are challenges that need to be solved in order to make effective use of these data for applications of AI. One of the biggest challenges in this space is a well-quantified cohort dataset that can help train algorithms with a “true” pattern. For instance, if we had high resolution datasets from patients where we collected a multitude of “omics” information and had corresponding longitudinal clinical data, we could then use these datasets to train our AI systems and generate novel insights and accelerate drug discovery.

As of today, there are no successes of AI-driven drugs either approved by the FDA or even in development so companies are reluctant to broadly adopt AI-based approaches in their R&D programs. Once there are a couple of success stories, we should see expansion of such approaches into regular workflows. The good news is that there is strong interest from pharma and biotech to see whether AI can help. We are seeing adoption of AI approaches in discrete parts of the R&D pipeline – from early stages of discovery, to clinical development at smaller scale vis à vis pilot projects. However, we are far from the point where AI can fully automate the drug discovery process and there still is a great need for people skilled in understanding the positive attributes and limitations of AI to make best use of the output of these technologies. And, the lack of people cross-trained in both AI and traditional drug discovery and development is another barrier to broad adoption of AI.

Q: Is there anything else you would like to share with the PMWC audience?

A: I think it’s important to demystify what AI is. Many people interchangeably use many different terms to refer AI such as machine learning, cognitive computing, Big Data or data sciences. Artificial Intelligence or machine learning is a set of software tools that enable us to find patterns in data – either patterns one might be trying to look for or patterns one didn’t know or wasn’t expecting to find. For instance, one could train software to look at measurements from patients who went on to do poorly with a treatment and then use the trained system to look for new patients who might be predicted to do poorly. Identifying patient types early on could be useful as it could help doctors as they consider optimal treatment options, and in turn, could save precious time and possibly extend patients’ lives. We need to think of AI as an important tool in a toolkit – it is only useful if we clearly define the problem we are trying to solve, and the end users are trained to understand both its benefits and limitations.

At the end of the day, the true value of AI to the end user – the patient – is not how we come up with an effective drug but how soon we do so. To that end, AI is a great tool that, if used correctly with the right data sets, can yield revolutionary therapies for the people who need them the most.

Interview with Ilan Kirsch of Adaptive Biotechnologies

Q: The Nobel Prize in Medicine was awarded recently to James Allison and Tasuku Honjo for their work on unleashing the body’s immune system to attack cancer, a breakthrough that has led to an entirely new class of drugs and brought lasting remissions to many patients who had run out of options. The Nobel committee hailed their accomplishments as establishing “an entirely new principle for cancer therapy.” What is your first-hand experience the impact that those new drugs had on patients?

A: For decades cancer was viewed as solely a cell-autonomous condition.

Read More

BMS buys Celgene | Lilly buys Loxo Oncology – Does this Signal a Return to Strong Deal-Making Activities in 2019?

Bristol-Myers Squibb’s blockbuster $74B deal to buy Celgene creates an oncology powerhouse amid industrywide excitement about the rapidly evolving science and explosive growth of the sector. The agreement could signal a return to deal-making for the pharmaceutical industry in the $133B global oncology therapeutics market.

Read More

Interview with Gini Deshpande of NuMedii

Q: What need is NuMedii addressing?

A: NuMedii, has been pioneering the use of Big Data, artificial intelligence (AI) and systems biology since 2010 to accelerate the discovery of precision therapies to address high unmet medical needs. Artificial Intelligence approaches are a natural fit to harness Big Data as they provide a framework to ‘train’ computers to recognize patterns and sift through vast amounts of new and existing genomic

Read More

Interview with Minnie Sarwal of UCSF

Q: Genomic medicine is entering more hospitals and bringing with it non-invasive technology that can be used to better target and treat diseases. What are some key milestones that contributed to this trend?

A: Completion of complete sequence data from the human genome project, and the advances in proteomic, microRNA and epigenetic assays added a layer of pathway biology to the understanding of human diseases.

Read More

Interview with Shidong Jia of Predicine

Q: Once sequencing has been validated as a clinical solution via trusted workflows, and coinciding with the technological developments driving costs lower, we can expect accelerated human genome profiling for clinical Dx. How soon, do you think, will we see accelerated growth and what can we expect?

A: We will see accelerated human genome profiling for clinical Dx in 2019 and the coming years as more biomarker-based cancer drugs are gaining approval.

Read More

Interview with Iya Khalil of GNS Healthcare

Q: Artificial intelligence (AI) techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. Do you believe that human physicians will be replaced by machines in the foreseeable future? What are your thoughts?

A: I think that there’s a lot of speculation and uncertainty around AI, but I don’t foresee a time when we won’t need physicians.

Read More

Interview with Ilya Michael Rachman of Immix Biopharma Inc.

Q: The Nobel Price in Medicine was awarded recently to James Allison and Tasuku for their work on unleashing the body’s immune system to attack cancer, a breakthrough that has led to an entirely new class of drugs and brought lasting remissions to many patients who had run out of options. The Nobel committee hailed their accomplishments as establishing “an entirely new principle for cancer therapy.” Besides CAR T-cell therapy what do you think next generation immunotherapies will look like to successfully combat cancer?

A: The next generation of immunotherapies will build on the insights discovered by immunologists like James Allison and Tasuku Honjo and extend them to modify the body’s response to tumors.

Read More

Join me to Kick off PMWC Silicon Valley in the Santa Clara Convention Center, Focusing on Every Element of Precision Medicine

My team worked in collaboration with Bill Dalton, Kim Blackwell, Atul Butte / India Hook Barnard, Nancy Davidson and Sharon Terry to create a program that touches every component of precision medicine while bringing together all of its key stakeholders. Leading participating institutions including Stanford Health Care, UCSF, Duke Health, Duke University, John Hopkins University, University of Michigan and more will share their learnings and experiences and their successes and challenges, as they make precision medicine the new standard of care for all.

Read More

Interview with Dominic Eisinger of Myriad RBM

Q: The Nobel Price in Medicine was awarded recently to James Allison and Tasuku for their work on unleashing the body’s immune system to attack cancer, a breakthrough that has led to an entirely new class of drugs and brought lasting remissions to many patients who had run out of options. The Nobel committee hailed their accomplishments as establishing “an entirely new principle for cancer therapy.” Besides CAR T-cell therapy what do you think next generation immunotherapies will look like to successfully combat cancer?

A: Next generation immunotherapies include CAR-Ts, TCRs, cancer vaccines, ADCs, bi-specific antibodies, and checkpoint inhibitors.

Read More

2018 Year in Review Milestones: Stakeholder Partnerships Carving Precision Medicine’s Future

2018 has clearly been a year when significant opportunities intersected with strong partnerships to yield advancements. In particular, the clinical advancements that were realized are a testimony to stakeholders working together to deliver on promises affecting major aspects of precision medicine. 2018 has clearly been a year when significant opportunities intersected with strong partnerships to yield advancements.

Read More

Interview with Lisa Alderson of Genome Medical

Q: Tell us a little bit about Genome Medical. What market need is Genome Medical addressing and how?

A: Genome Medical is a telegenomics company that is bridging the gap between available, genetic expertise and the clinical application of genomics.

Read More

Interview with Nasir Bhanpuri of Virta Health

Q: What need is Virta Health addressing?

A: Virta Health delivers an evidence-based treatment to safely and sustainably reverse type 2 diabetes without the use of medications or surgery. In the U.S. alone, type 2 diabetes and prediabetes affects 115 million people, and the economic burden is well-over $300 billion and growing.

Read More

Interview with Jussi Paananen of Blueprint Genetics Inc.

Q: Artificial intelligence (AI) techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. Do you believe that human physicians will be replaced by machines in the foreseeable future? What are your thoughts?

A: Right now, we are looking at merely a fragment of clinical work that could be replaced by a machine.

Read More

Our Healthcare System Clearly Needs a Revamp And It’s Happening!

Patients are demanding an exceptional healthcare experience; one that makes care more. At PMWC, we can sense a revolution in the healthcare system on the horizon with fee-for-service losing dominance and innovative technology playing a key role in healthcare delivery.

Read More

Interview with Sebastian Kronmueller of Siemens Healthineers

Q: Artificial intelligence (AI) techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. Do you believe that human physicians will be replaced by machines in the foreseeable future? What are your thoughts?

A: Human physicians will certainly not be replaced by machine learning or AI technologies.

Read More
Johns Hopkins
University Of Michigan

The Precision Medicine World Conference (PMWC), in its 16th installment, will take place in the Santa Clara Convention Center (Silicon Valley) on January 20-23, 2019. The program will traverse innovative technologies, thriving initiatives, and clinical case studies that enable the translation of precision medicine into direct improvements in health care. Conference attendees will have an opportunity to learn first-hand about the latest developments and advancements in precision medicine and cutting-edge new strategies and solutions that are changing how patients are treated.

Agenda highlights:

  • Five tracks will showcase sessions on the latest advancements in precision medicine which include, but are not limited to:
    • AI & Data Science Showcase
    • Clinical & Research Tools Showcase
    • Clinical Dx Showcase
    • Creating Clinical Value with Liquid Biopsy ctDNA, etc.
    • Digital Health/Health and Wellness
    • Digital Phenotyping
    • Diversity in Precision Medicine
    • Drug Development (PPPs)
    • Early Days of Life Sequencing
    • Emerging Technologies in PM
    • Emerging Therapeutic Showcase
    • FDA Efforts to Accelerate PM
    • Gene Editing
    • Genomic Profiling Showcase
    • Immunotherapy Sessions & Showcase
    • Implementation into Health Care Delivery
    • Large Scale Bio-data Resources to Support Drug Development (PPPs)
    • Microbial Profiling Showcase
    • Microbiome
    • Neoantigens
    • Next-Gen. Workforce of PM
    • Non-Clinical Services Showcase
    • Pharmacogenomics
    • Point-of Care Dx Platform
    • Precision Public Health
    • Rare Disease Diagnosis
    • Resilience
    • Robust Clinical Decision Support Tools
    • Wellness and Aging Showcase

Agenda highlights:

    • Five tracks will showcase sessions on the latest advancements in precision medicine which include, but are not limited to:
      • AI & Data Science Showcase
      • Clinical & Research Tools Showcase
      • Clinical Dx Showcase
      • Creating Clinical Value with Liquid Biopsy ctDNA, etc.
      • Digital Health/Health and Wellness
      • Digital Phenotyping
      • Diversity in Precision Medicine
      • Drug Development (PPPs)
      • Early Days of Life Sequencing
      • Emerging Technologies in PM
      • Emerging Therapeutic Showcase
      • FDA Efforts to Accelerate PM
      • Gene Editing / CRISPR
      • Genomic Profiling Showcase
      • Immunotherapy Sessions & Showcase
      • Implementation into Health Care Delivery
      • Large Scale Bio-data Resources to Support Drug Development (PPPs)
      • Microbial Profiling Showcase
      • Microbiome
      • Neoantigens
      • Next-Gen. Workforce of PM
      • Non-Clinical Services Showcase
      • Pharmacogenomics
      • Point-of Care Dx Platform
      • Precision Public Health
      • Rare Disease Diagnosis
      • Resilience
      • Robust Clinical Decision Support Tools
      • Wellness and Aging Showcase
  • Luminary and Pioneer Awards, honoring individuals who contributed, and continue to contribute, to the field of Precision Medicine
  • 2000+ multidisciplinary attendees, from across the entire spectrum of healthcare, representing different types of companies, technologies, and medical centers with leadership roles in precision medicine
Get Updates
Sign up for occasional updates on upcoming conferences, news, and other information.
We respect your privacy and will never share your email with anyone.
Something went wrong, please verify your input.
Thank you for signing up!

Don't Miss Important Precision Medicine Updates

PMWC is the most comprehensive precision medicine conference. To receive the lastest news and updates from the field, subscribe to the newsletter here.

You have Successfully Subscribed!