Predictive Oncology looks to improve precision cancer Rx development with AI-driven platform

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As appeared in Precision Oncology News.

NEW YORK – Predictive Oncology wants to ink more partnerships with biopharmaceutical companies and demonstrate the ability of its commercially available PEDAL platform to provide early insights that sponsors can use to prioritize drugs for development and identify biomarker-informed indications.

Predictive Oncology’s Patient-centric Drug Discovery by Active Learning (PEDAL) platform uses artificial intelligence and a proprietary biobank to generate drug response predictions. Predictive Oncology CEO Raymond Vennare said in a conference call last month that the company believes its biobank is the largest of its kind in the world. “There are certainly larger biobanks, but not with the kind of tumor-specific information and data associated with it,” he said.

Eagan, Minnesota-headquartered Predictive Oncology aims to leverage the PEDAL platform for its biopharma clients and help them use it to decide early on which drugs to prioritize for development and which to discontinue. “This artificial intelligence is going to allow the biopharma partner to be able to predict what are the drugs that they should be moving into development,” Pamela Bush, senior VP of strategic sales and business development, said in an interview. “We’re providing that richness of tumor diversity and the population diversity that normally the companies will not be able to see until they are in a clinical trial and [the drug is] challenged against a multitude of different patients.”

With its technology, the company wants to change the way that biopharma companies plan clinical trials and develop oncology drugs. “This is all about getting the right drugs to the right patients at the right time as soon as possible to personalize the treatment of their therapies, primarily in oncology,” said Vennare.

Bush pointed out that approximately 95 percent of drugs that enter clinical trials eventually fail. That means a lot of wasted effort and resources for drugmakers given that even before a molecule enters Phase I trials, typically five to eight years of development have already been invested in the product. Because pharma companies can’t predict which early-stage drug candidates will succeed, they end up playing a “numbers game,” according to Bush, by advancing multiple compounds.

“One in 20 [molecules] is actually going to be able to make it into a medicine that actually goes into patients. … What happens if we are able to provide information to the pharmaceutical company that doubles that [and] one in 10 molecules actually make it?” Bush said. “Imagine if you take information all the way [back] to the discovery process and make better decisions so that you only select the [molecules] that are most likely to succeed.”

That not only adds up to millions of dollars saved in clinical trials that no longer need to be carried out, Bush said, but it provides additional returns on the same money invested by identifying drug candidates with a higher likelihood of reaching the market. Moreover, with the help of the biobank, drugmakers can have earlier insights into the safety and efficacy of their therapies against a set of tumor samples representing the heterogeneity of response found in a larger population. According to Bush, this will get medicines to patients faster.

Another important feature of the biobank is that while the supply of each tumor cell sample is theoretically finite, the cells don’t lose features of the original tumor response — an issue affecting cell lines currently used by pharmaceutical companies in preclinical testing that are made immortal through continuous regrowth in new media (also known as passaging).

The way that the platform will work for customers is that Predictive Oncology will provide a representative selection of tumor samples for the target the drugmaker is interested in. The customer provides the therapeutic compounds they want to test against the samples. The company then uses the platform to generate response predictions and carries out a select series of experiments iteratively until a high confidence prediction is achieved.

In a proof-of-concept study, Predictive Oncology assessed 175 drugs already approved by the US Food and Drug Administration alongside 130 ovarian tumor samples. However, investigators did not directly test each drug against each sample. “If you line up on the X axis the drugs and you line up all of the tumor samples on the Y axis, that would be the equivalent of doing 23,000 combination experiments in the lab,” Bush said. “That is absolutely time and cost prohibitive.”

Instead, using PEDAL’s artificial intelligence capabilities, they produced a prediction of each possible combination. “It is not going to be necessarily a high confidence prediction for all of them,” Bush said, noting that low confidence predictions would then be tested in a wet laboratory experiment. Data from those experiments then go back into the system to generate a new set of predictions, and the process continues through multiple rounds until it settles into a high confidence prediction.

Although PEDAL is able to incorporate biomarker information up front in the process, it does not rely on that data input to produce biomarker predictions. “It can work with incomplete data,” Bush said. “At the end of the campaign, we can go deeper into the samples and understand what are the biomarkers and what are the features that are resulting in a response from a particular drug.”

In the study with ovarian tumor samples, Bush said investigators only needed to test about 3 percent of the potential drug-tumor sample combinations in the laboratory to produce high confidence predictions for 20 percent of the drug-tumor combinations over a period of three months.

The next step was to validate the predictions and learn whether the drugs really produce a response in the specific tumor type. Bush said the predictions turned out to be 92 percent accurate, based on which “a pharmaceutical company can say [whether] this is a molecule that works in enough samples that it is worth taking into a clinical trial.”

Instead of following a traditional path where drug testing begins in cell models, moves to animal models, and finally, advances into clinical studies, Bush said the PEDAL platform allows the pharmaceutical company to model clinical testing in thousands of patients. That model, according to Predictive Oncology, can point not only to the success or failure of a drug but also to optimal indications, and it can help rule out drugs that are unlikely to be effective. “This is going to disrupt the way that drug development is done,” Bush said, by changing the way companies choose drug indications.

Rather than guessing at the best indication for a drug and testing the hypothesis in clinical trials, drugmakers can use PEDAL data to make more precise predictions about successful indications. PEDAL will also provide insights about the genetic features of a tumor that can yield a strong response. Early biomarker identification leads to early validation and timely alignment and integration of biomarker strategies with the therapeutic development program, Bush said, adding that this strategy may allow drugmakers to carry out smaller trials to achieve the same statistical power.

“It’s saving thousands of hours preclinically, and it’s saving millions and millions of dollars,” said Predictive Oncology CFO Bob Myers. He noted that while there were 1,500 cancer drugs selected for clinical trials over the past 20 years, only 115 were approved. “We can improve on that. We can cut the time. We can cut the cost.”

Predictive Oncology’s business strategy now is to upsell current biopharma customers who are already using its 3D tumor modeling capabilities. “Our objective now is to introduce the PEDAL technology into that existing customer base,” Vennare said, adding that the company is also pursuing smaller biopharma customers. “[PEDAL] probably has an equivalent, if not bigger, value for smaller companies that may have different budget latitudes.”

Although for reasons of practicality, Predictive Oncology is touting the money-saving advantages of its platform for pharmaceutical companies, Vennare said he hopes that will translate to cost savings for patients, too. “Our job is to make it more accessible, less expensive, and more efficient for pharmaceutical companies to develop drugs quickly [and] get it in the hands of clinicians and patients,” he said. “Unfortunately, we have no control over whether or not those cost savings will translate into [a lower] cost of the drug [for the patient] at the end of that journey. Our hope is they will.”


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David S. Smith


David S. Smith, JD, is a life sciences and intellectual property attorney, veteran biotech industry executive and leading authority on the legal issues surrounding the therapeutic use of human tissue and cells. He has extensive transactional experience, venture financings and regulatory matters for life sciences companies and investors.

Mr. Smith frequently speaks on matters related to the commercial development of tissue, cell and stem cell technologies, and has authored extensively on topics like human tissue therapies and tissue engineering research. He currently serves on the Board of Directors with Foundation for Cell and Gene Medicine; is a current fellow and past member of the executive committee of Tissue Engineering and Regenerative Medicine International Society; was a member of the Board of Directors of the Pennsylvania Biotechnology Association; and was a past officer of the Pittsburgh Tissue Engineering Initiative.

“ Having worked in the healthcare industry for over 30 years, helping the companies who deliver patient care utilize the best technology, improve their processes and receive all the revenue they can within all compliance standards;
I was excited to join Predictive Oncology’s Board of Directors in helping to guide this exciting company with all of their cutting edge capabilities for improving
the health care of patients
with cancer.”

Pamela Bush, Ph.D.

SVP, Strategic Sales and Business Development,

At Predictive Oncology

Pamela Bush comes with more than twenty years of experience in venture creation, finance, and business development in the life sciences industry. At POAI, she leads the sales efforts and business development activities across the portfolio.

Before Predictive Oncology

Prior to joining POAI Pamela worked at Eli Lilly & Company in various roles including Corporate Business Development, Finance and Patient Services. In addition to her Lilly work experience, Pamela has worked in economic development, academia, and business consulting supporting the creation and growth of 80+ life sciences start-ups.

“ POAI has developed solutions to help biopharma partners increase the probability of success of their oncology pipeline.”

Carnegie Mellon University

Ph.D., Molecular Biology
MBA, Tepper School of Business

Lawrence J. DeLucas, Ph.D

Predictive Oncology
President, Soluble Biotech
At Predictive Oncology

Dr. DeLucas is the Vice president of Operations for Predictive Oncology and President and co-founder of Soluble Biotech, Inc. DeLucas is currently working to complete development of GMP facilities at Soluble Biotech and at TumorGenesis. In addition, he oversees Soluble Biotech’s solubility and stability contracts for numerous pharmaceutical/biotech companies.

Before Predictive Oncology

From 1981-2016 Dr. DeLucas was a faculty member at the University of Alabama at Birmingham (UAB) where he served as a Professor in the School of Optometry, Senior Scientist and Director of the Comprehensive Cancer Center X-ray Shared Facility, and Director of the Center for Structural Biology. Dr. DeLucas received five degrees from UAB culminating in a Doctor of Optometry degree and a Ph.D. degree in Biochemistry. He also received honorary Doctor of Science degrees from The Ohio State University, Ferris State University, the State University of New York (SUNY), and the Illinois College of Optometry. He has published 164 peer-reviewed research articles in various scientific journals, co-authored and edited several books on protein crystal growth and membrane proteins and is a co-inventor on 43 patents involving protein crystal growth, novel biotechnologies and structure-based drug design. DeLucas was a payload specialist NASA astronaut and member of the 7-person crew of Space Shuttle Columbia for Mission “STS-50”, called the United States Microgravity Laboratory-1 (USML-1) Spacelab mission. Columbia launched on June 25, 1992, returning on July 9.  In 1994 and 1995, Dr. DeLucas served as the Chief Scientist for the International Space Station at NASA Headquarters in Washington, D.C. In 1999, Dr. DeLucas was recognized as one of the scientists who could shape the 21st century in an article published by “The Sunday Times” of London titled “The Brains Behind the 21st Century.”  In 2004, he was recognized as a Top Ten Finalist for the Entrepreneur of the Year award from the Birmingham Business Journal. 

“ Soluble Biotech is continually demonstrating to pharmaceutical and biotech companies the significant value of its novel HSC technology for optimizing protein therapeutic formulations to treat a variety of chronic and infectious diseases. ”

  • Five degrees from Univ. of Alabama at Birmingham (UAB): B.S. Chemistry, M.S. Chemistry, B.S. Physiological Optics, O.D. Optometry, Ph.D Biochemistry
  • Published 164 peer-reviewed research articles in various scientific journals
  • 1993-2016: Director of the UAB Comprehensive Cancer Center X-ray Shared Facility, and Director of the Center for Structural Biology
  • NASA Astronaut, flew on Columbia Space Shuttle
  • 1994-1995: Appointed Chief Scientist for the International Space Station at NASA HQ

Arlette Uihlein, MD, FCAP, FASCP

Dr. Arlette Uihlein is Senior Vice President of Regulatory Affairs and Quality for Predictive Oncology and Site Leader of Helomics, serving as the Vice President of Operations, Pathology Services and Medical Director of Helomics® Clinical and Research Labs since 2011. Dr. Uihlein is Board Certified in Anatomic and Clinical Pathology, Cytopathology and Family Medicine. Dr. Uihlein completed her Pathology Residency at Allegheny General Hospital, where she served as Chief Resident in Pathology and completed Fellowships in Cytopathology and Surgical Pathology. During that time, she conducted extensive clinical research involving molecular pathology diagnostic and predictive markers, imaging of solid tumors, and novel applications of cellular tumor markers. While serving as Medical Director at Helomics, a CLIA and New York State certified lab, Dr. Uihlein has published research in molecular assay development, lab automation, and tissue and cell processing. She is a Designated Civil Surgeon for the U.S. Dept. of Justice and a certified Medical Review Officer for the Department of Transportation. She is a Fellow of the College of American Pathologists and the American Society of Clinical Pathology, NYSDOH Certificate Qualified, and a member of ASCO.

“ At Helomics we’re delivering better-informed decision making saving pharma time and money, while providing cancer patients with appropriate therapies.”




Medical College of Ohio
Doctor of Medicine

Baldwin-Wallace University
BS, Biology

Richard Gabriel, BS, MBA

Predictive Oncology
Site Leader, TumorGenesis
At Predictive Oncology
My role at Predictive Oncology is to bring the business sense to managing Research and Development programs at all our companies. To seek new ways and opportunities to commercialize exciting new technologies that we have built, licensed, acquired, or are developing through our own research and development. The success of any company is to get the research off the bench and to the customers. That is what I do at POAI and help the other companies as well.
Before Predictive Oncology
Prior to starting his first company in 1984 and registering with the FDA a pilot plant facility to make pharmaceutical actives, Mr. Gabriel managed a $50 million product line for W.R. Grace, developed new marketing and sales strategies for Ventron a Division of Morton Thiokol, research work at Ashland Chemical for pressure sensitive adhesives and plant scale-up. Since then, he ran a genetics company, built three GMP/Research facilities, and helped 5 drugs reach their markets in AIDS and cancer. Real expertise in cGMP process scale-up and compliance. Completely understand the needs of an API manufacturing facility and build processes that are scalable, environmentally acceptable, and safe. 3 FDA inspections with no 483’s, ISO certification, DEA registration, DoD compliance, NCI contractor and inventor. Has also broad-based experience in start-up companies and how to make them operational and profitable. 7 years of Team set-up, R&D management, and implementation for 165-person (85 PhD’s and Engineers) company (Pharm-Eco) and lecturer on cGMP and Teams within the Pharmaceutical Industry.

“ Patients are always first, is our driving force. Oncology is a tough space, and we are determined to bring the best validated science to help cancer patients and as our CEO says, ‘Eliminate Cancer.’ That takes teamwork and a lot of smart hard-working people, our team members at POAI are up to the challenge. ”



Suffolk University
Executive MBA Program

Ohio Dominican College
BS, Chemistry

Ohio State University
Microbiology and Virology

University of Cincinnati
Associates Degree, Liberal Arts

Bob Myers, BBA, MBA

Predictive Oncology
Site Leader, Skyline Medical
At Predictive Oncology

Executive Officer, Compliance Officer, Corporate Secretary, and member of the Senior Leadership Team. Responsible for Finance, Administration, Human Resources, Investor Relations, and IT. Skyline Medical Site Leader.

Before Predictive Oncology

Numerous years as CEO/Controller consultant including medical devices companies. Executive positions with CES Computer Solutions, Computer Accomplishments, Hi-Tech Stationary & Printing, Capital Distributors Corp, International Creative Management American Express, Showtime Entertainment and public accounting with Laventhol & Horwath, CPA’s.

“ It’s a privilege to work with a highly talented team to pursue oncology advances, while protecting and increasing shareholder value. ”


Adelphi University
MBA, Finance

Hofstra University
BBA, Public Accounting 

Raymond Vennare

Predictive Oncology
At Predictive Oncology

Raymond F. Vennare became Predictive Oncology’s CEO and Chairman of the Board on November 1, 2022. He has served on the Board of Directors since September of 2021.

Mr. Vennare brings more than thirty years of experience as an accomplished senior executive, board director and biotechnology entrepreneur. As a seasoned professional who has founded, built and managed multiple companies on behalf of institutional investors, private foundations and research institutions, Mr. Vennare has a long history of leading companies that range from bioinformatics, diagnostics and therapeutic drug delivery to FDA-cleared medical devices. Throughout his career, Mr. Vennare has played a key role in the capitalization, development and commercialization of innovative and novel technologies.

Since 2015, Mr. Vennare has served as CEO and Chairman of Cvergenx, Inc., a genomic informatics company developing decision-support tools for radiation oncology, and is currently an Investment Partner in Inventeur, LLC, a holding company of medical technologies in anesthesiology. Mr. Vennare’s previous experience includes co-founding ThermalTherapeutic Systems, Inc., where he served as President and Chief Executive Officer, President and Chief Executive Officer of ImmunoSite, Inc., Senior Vice President and Chief Information Officer of TissueInformatics, Inc., and President of VS/Interactive.


Mr. Vennare earned his undergraduate degree from the University of Pittsburgh (BA) and holds graduate degrees from Duquesne University (MS) and Case Western Reserve University (MA).

What we do for our customers today will directly impact the lives of those patients who may benefit by these discoveries in the future.”