A Machine Learning / Drug Discovery Company

Shortening the Drug Discovery timeline through advanced machine learning techniques

ML/AI-based Drug Design

Spektron Systems’ approach shortens discovery timelines from 4.5+ years to approximately 1 year. We target a $10M cost of discovery opposed to $100M+. Our approach shows a strong potential to disruptively improve pharmaceutical pipeline success.

A Platform for Drug Design

Spektron Systems has developed a platform, Q-MAP™, for designing new molecules which we will carry through pre-clinical testing.  Q-MAP™ is designed to be generally agnostic to therapeutic drug class.

Drug Discovery's Dilemma

The average cost of introducing a new drug has reached $2.6 billion. Pre-clinical trials alone can cost up to $1+ billion. Glacially slow discovery takes 4.5+ years per drug because traditional methods focus on scarce “low-hanging fruit”. Investment returns are low and dropping.

A Solution

It is generally considered that Machine Learning (ML)  and Artificial intelligence (AI)  based approaches replace “brute force” experimentation and “needle in a haystack” luck with precise, directed design via vastly more efficient drug engineering solutions. Only one company—Spektron Systems — works closely with the FDA to establish reliable, repeatable methods for predictive toxicology and cost-effective new ML/AI drug discovery.

The Leadership Team

David Wolf, M.D.

President / Chief Medical Officer

David Wolf, M.D.

He is a licensed physician, astronaut, electrical engineer and life sciences, inventor/researcher. His experience includes leadership positions as Chief Engineer and Program Manager for NASA programs, board level program management responsibility and influence and oversight for multiple, national and international, endeavors within NASA. Dr. Wolf was the recipient of the NASA Inventor of the Year in 1992. He has a B.S. in Electrical Engineering from Purdue University and an M.D. from Indiana University School of Medicine.

Robert Cain

EVP / Chief Strategy Officer

Robert Cain

Robert Cain is an MBA with background in investment banking, IPOs and pharmaceuticals, and experience in strategy, finance and business development for companies ranging from startups to Fortune 500. He holds a B.A. from Harvard and an MBA from The Wharton School of the University of Pennsylvania.

Tim Dockins

Chief Operating Officer

Tim Dockins

Tim Dockins is a polyglot programmer with an emphasis on complex data manipulation and visualization. He has an extensive background in several specialty areas, including, predictive modeling, machine learning and pattern classification, UI design and implementation, data science, and program management. Tim received a B.S. in Computer Science from the University of Texas at Arlington. He is a Ph.D. Candidate in the Computer Science and Engineering department at the same university where he studies intelligent systems and machine learning.

Bob D'Agostino, M.Sc.

Director, Machine Learning

Bob D'Agostino

Bob D'Agostino leads the ML/AI platform development. He has over 15 years of experience leading/implementing scientific computing projects for a variety of industries and applications, including drug discovery, defense, chemical detection, semiconductors, and the automotive industry. He has a B.S. in Physics from Syracuse University and an M.S. in Applied Mathematics from the University of Massachusetts Lowell.

W. Ken Fang, Ph.D.

Principal Chemist

W. Ken Fang, Ph.D.

A research scientist with over 20 years of experience of designing new innovative drugs for treating neuropathic pain, CNS diseases, inflammation, ocular and skin diseases. Dr. Fang has comprehensive expertise in small molecule HTS hit identification, lead generation, and optimization based on target selectivity, ADME, toxicology, preclinical safety, and in vivo pharmacology. He has extensive experience in parallel synthesis techniques, and broad experience in preparation of patent applications and publication manuscripts with over 52 patents.

Ashley Meyer, M.Sc.

Principal Informatics Scientist

Ashley Meyer, M.Sc.

Ashley Meyer acquired her B.S. in Biology from the University of Arkansas at Little Rock (UALR), and her M.S. in Biology with an emphasis in Evolutionary Ecology from the University of Louisiana at Monroe (ULM). Her varied specialties include bacterial culturing and testing, radio telemetry, transmitter and PIT tagging, and collection and curation of morphometric data for invertebrates. Meyer served as an instructor of Microbiology and Human Anatomy and Physiology at ULM and Pulaski Technical College.

Max Sharifi, Ph.D.

Senior Computational Chemist

Max Sharifi, Ph.D.

Dr. Sharifi leads computational modeling and molecular design efforts. His expertise is in developing toxicity models using a variety of machine learning techniques. He works closely with medicinal chemists and pharmacologists to have an accurate computational chemistry-driven decision making in lead generation. He has a M.Phil and Ph.D. in Pharmacy from Kent University with an emphasis in computational chemistry and drug design.

Contact Us

Mailing Address
400 West Capitol Ave
17th Floor
Little Rock, AR 72201
(800) 972-0751

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