Transcripta Bio, an AI-powered drug discovery company focused on neurological and neuromuscular diseases, today announced additions to its Scientific Advisory Board (SAB). The SAB includes leaders with expertise in human genetics, transcriptomic biology, clinical drug development, and neuromuscular clinical trial design.

The SAB will help guide Transcripta’s scientific and clinical strategy as the company advances its pipeline toward the clinic, drawing on its closed-loop discovery engine. The engine uses transcriptomic signature matching to identify drug candidates whose molecular profiles are the inverse of patient-derived disease signatures. The platform combines a Disease Signature Atlas built from patient single-cell RNA sequencing data, a Drug-Gene Atlas mapping the full transcriptomic response of clinically tested and novel compounds, and Conductor AI, a machine learning system trained on more than one billion gene responses.

The SAB members are:

  • Anthony Accorsi, Ph.D. | Venture Partner, Blackbird Laboratories

    A former Head of Muscle Biology at ReNAgade Therapeutics and Fulcrum Therapeutics as well as currently serving as CSO of NuGate Therapeutics, Dr. Accorsi has driven programs from gene target to IND across multiple modalities and diseases — bridging human genetics and druggable biology for Transcripta’s pipeline.

  • Matt Deardorff, M.D., Ph.D. | Professor at University of Southern California and Director of Personalized Care at Children’s Hospital Los Angeles

    A clinical geneticist and molecular biologist, Dr. Deardorff has spent the last 20+ years identifying and investigating the genetic and cell biological basis of a number of rare disorders of syndromic intellectual disability. Currently, as the Director of Personalized Care at the Children’s Hospital of Los Angeles, he is passionate about applying genomic medicine to pediatric care and increasing therapeutic options for children with rare disorders.

  • Daniel Geschwind, M.D., Ph.D. | Distinguished Professor, Associate Vice Chancellor and Director of UCLA Institute for Precision Health

    A pioneer in transcriptomic and genomic analyses of CNS disease, Dr. Geschwind chaired PsychENCODE and also directs the UCLA Center for Autism Research and Treatment and an NIH Autism Center of Excellence Network. His expertise anchors Transcripta’s Disease Signature Atlas in CNS biology.

  • Michael Graziano, Ph.D. | Principal at MPG Pharma Consulting LLC

    Dr. Graziano, most recently SVP and Chief Scientific Officer, Valo Health, led cardiometabolic discovery at Schering-Plough, served as VP of Research Biology at MyoKardia prior to its $13 billion acquisition by Bristol Myers Squibb, and has contributed to two drug approvals. He brings a proven CSO playbook for AI-driven drug discovery.

  • John Hadcock, Ph.D. | Interim Chief Scientific Officer of Transcripta Bio; President & Founder of Veritas Biosciences Solutions LLC

    Spanning leadership roles at Wyeth, Pfizer, Novartis, Ironwood, Cyclerion, Sarepta, and Prime Medicine, Dr. Hadcock brings deep translational and precision medicine expertise. He has contributed to five drug approvals and over 15 first-in-human studies spanning CNS, neuromuscular, and broad and rare metabolic diseases. He guides Transcripta’s path from Drug-Gene Atlas hits to IND-ready development packages.

  • Elizabeth Iorns, Ph.D. | Co-Founder and CEO of Familiar Therapeutics

    As co-founder and CEO of Science Exchange, Dr. Iorns built the operating infrastructure for outsourced biology at scale and founded the Reproducibility Initiative. Named to Nature’s “10 Who Mattered,” she brings the industrial rigor underlying Transcripta’s platform of more than one billion experiments.

  • Michelle Mellion, M.D. | Chief Medical Officer of AstronauTx

    A former CMO of PepGen and Executive Medical Director at Fulcrum Therapeutics, Dr. Mellion has designed Phase I through Phase III neuromuscular trials at Fulcrum, Vertex, and Biogen. She closes the loop from preclinical signal to clinical execution.

  • Ian Watson, Ph.D. | Machine Learning & Computational Chemistry

    With more than 25 years applying machine learning to small molecule drug discovery, Dr. Watson spent two decades at Eli Lilly building core computational infrastructure, including large scale chemical similarity tools and the widely used Lilly Medchem Rules, and joined Google, working on A/I applications, including close collaboration with Google’s Accelerated Science team. He brings deep computational chemistry expertise to Transcripta’s Conductor AI and its search across billions of synthesizable compounds.

“Drug discovery has a systemic failure problem, and fixing it requires people who have lived that failure firsthand and understand where it starts,” said Chris Moxham, founder and CEO of Transcripta Bio. “Each member of this board has operated at the exact intersection where our platform creates value — where human genetics meets druggable biology, where preclinical data either earns or loses clinical credibility. Their experience sharpens every layer of what we’re building.”

Transcripta Bio’s closed-loop discovery engine is designed to use transcriptomic signature matching to identify drugs whose molecular signatures are the inverse of patient-derived disease signatures. The platform combines a Disease Signature Atlas built from actual patient single-cell RNA sequencing data, a Drug-Gene Atlas mapping the full transcriptomic response of FDA-approved and novel compounds, and Conductor AI, a machine learning system trained on more than one billion gene responses that begins at lead optimization rather than hit identification. Together, these three components systematically assess compounds, with the goal of de-risking drug development by addressing the root causes of clinical failure before candidates ever reach the clinic.

Transcripta Bio’s pipeline spans four programs across Huntington’s Disease, Autism Spectrum Disorder, Myotonic Dystrophy, and Facioscapulohumeral Muscular Dystrophy (FSHD), with clinical trial initiation targeted for its ASD and FSHD programs in 2027.

About Transcripta Bio

Transcripta Bio is an AI-powered drug discovery company developing treatments for neurological and neuromuscular diseases. The company’s closed-loop discovery engine uses transcriptomic signature matching to identify drug candidates whose molecular signatures are the inverse of patient-derived disease signatures, enabling a faster, more capital-efficient path to the clinic. Transcripta Bio’s pipeline spans four programs including Myotonic Dystrophy, Facioscapulohumeral Muscular Dystrophy (FSHD), Autism Spectrum Disorder (ASD), and Huntington’s Disease (HD). The company is based in Palo Alto, California. For more information, visit transcriptabio.com.

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