Panna Sharma, Lantern Pharma

Panna Sharma Panna Sharma is the President, Chief Executive Officer and Board member of Lantern Pharma, a clinical stage oncology biotech using artificial intelligence (AI) and genomics to innovate the rescue, revitalization and development of precision cancer therapeutics. Lantern is focused on improving patient outcomes by using its proprietary AI platform – Response Algorithm for Drug Repositioning & Rescue (RADR™) – to rescue, revitalize and develop abandoned or failed cancer drugs, and to accelerate their development through precision trials that help identify patient groups more likely to respond to its pipeline of targeted cancer therapies.

As Chief Executive Officer, Panna is responsible for developing Lantern’s strategic vision, and working closely with the venture investors to raise capital that will place the Company at the forefront of using AI and genomics in developing its pipeline of precision therapies. The Lantern Pharma (LP) pipeline currently includes three drugs – two in clinical stages and one in preclinical, all focusing on cancers that have unique and unmet clinical needs with a clearly defined patient population. These drugs can be targeted to patients whose profile identifies them as having the highest probability of benefiting from the drug, thereby achieving better outcomes with reduced costs and accelerated timelines.

Prior to joining Lantern in 2018, Panna was the President and Chief Executive Officer of Cancer Genetics, Inc. (Nasdaq: CGIX), a provider of genomic and immune based cancer diagnostics and therapy development services some of the most prestigious medical institutions and pharma companies in the world. In his capacity as CEO at CGIX, he raised over $100 million in the public and private markets and grew the company from 25 employees in New Jersey to over 250 employees globally across multiple continents. Panna took CGIX public in 2013 and acquired four companies globally that help CGIX deliver on its mission to help personalize cancer treatment. Prior to CGIX, Panna founded TSG Partners, a specialty advisory group combining corporate strategy and corporate finance to create shareholder value for companies and investors in the life sciences, biotechnology and environmental sciences. Panna began his career as an industry analyst for financial services and technology companies, and was part of the management team that took the digital strategy and e-business company iXL public.

Panna attended Boston University in the University Professors Program having focused his studies on Philosophy of Science, Neural Networks and Artificial Intelligence. When not focused on the future of biotech, machine learning, emerging technologies and genomics, Panna can be found with his three children and wife and listening to music, attending sports functions, discussing new and ethical uses of AI, and enjoying the vibrant food scene in Atlanta.

Session

3:55 PM - 4:25 PM

An AI Powered Project: Human Genetics & Drug Discovery

This session will discuss various projects and their potential impact on the industry when the big data derived from the human genome is married with breakthroughs from artificial intelligence.

Moderator

  • Dr. Gunaretnam (Guna) Rajagopal

    Dr. Gunaretnam (Guna) Rajagopal VP Global Head – Computational Sciences, Discovery Sciences Janssen Research & Development, A Johnson & Johnson Company

Panel

  • John Reynders

    John Reynders Vice President, Data Science, Genomics, and Bioinformatics Alexion Pharmaceuticals, Inc.

    • Answering the question “how many rare diseases are there?” and navigating the rare-disease landscape with data sciences
    • If Amazon can recommend a book we might like, can we use AI to help a doctor ask the next right question to enable a rare-disease diagnosis?
    • How to set a world record in rare-disease diagnosis – hint: genomics + AI
  • Panna Sharma

    Panna Sharma CEO Lantern Pharma

    • How Lantern Pharma is revolutionizing the drug development process by implementing its RADR platform, which leverages AI, ML and genomics, to increase clinical trial success rates as well as reduce timelines and costs.
    • Use Cases for drugs LP100, LP184 and LP300

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