How to Develop More Effective Cancer Treatments

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It’s never been a chip shot developing cancer treatments. In fact, only 7.78% of all cancer drugs that enter phase 1 clinical trials are ultimately approved by the U.S. Food and Drug Administration (FDA), according to the Pharmaceutical Manufacturers Association. Of the 1,481 cancer drugs selected for clinical trials between 2000 and 2020, only 115 were approved. In a world where that process costs nearly $650 million on average for a single cancer drug, a 92.22% rate of failure means billions of dollars and thousands of hours wasted. 

And the number of cancer drugs entering pre-clinical and clinical trials is on the rise. In 2020 23.1% of all clinical trials are oncology drug trials; that is up from 14.8% in 2000, according to ClinTrials.gov. In 2021, 1,300 drugs had been selected for pre-clinical and clinical trials. Without a change in approach, companies will continue wasting gargantuan amounts of resources in hopes they find that rare diamond in the rough.

Why is it that so many cancer drugs fail in clinical trials? And how can modern technology like artificial intelligence, 3D cell cultures, and novel approaches to tumor research improve the odds? After more than a century of research, we’re finally on the cusp of improving our ability to effectively discover and develop safe, effective cancer drugs not only for specific types of cancer, but also specific types of patients.

Why most cancer drugs fail to attain approval

 

Cancer is an extremely complex disease that evolves and changes as it grows. This makes it nearly impossible to create a one-size-fits-all cancer treatment that has a high rate of success across a diverse patient population.  

A new drug candidate that begins with a promising study in laboratory cell testing can quickly move into more expensive animal trials as companies try to advance their most promising projects. Even if it performs well in animal trials, that same drug can fizzle once it enters human trials (after significant investments in time and money have already been made). 

Moreover, even when a drug shows success in treating one patient demographic means nothing when it comes to treating patients with entirely different genetic backgrounds. Physicians from around the world have always known the drugs that work on a population with a genetic history based in Europe may have reduced efficacy or not even work at all for patients with genetic profiles rooted in the Middle East North Africa (MENA) region. 

Similarly, drugs used in traditional medicines in Eastern cultures often have no effect on Europeans and North Americans, except for those communities that originated from the East. In some cases, these drugs can even be toxic to patients with certain genetic profiles. 

Adding to this built in diversity or heterogeneity of the people with cancer, the cancer itself becomes highly diverse or heterogeneous. Dr. Mary Relling, Ph.D., and her team at St. Jude’s Hospital have identified a number of Single Polynucleotide Polymorphisms (SNPs) called ‘snips’, or changes in the DNA code amongst different adolescent patients, that shows the bad and good effects of having ‘inherited’ polymorphisms in your genetic code. These polymorphisms can cause a child to respond favorably or unfavorably to combination drug treatments for cancer.

Needless to say, all this makes it very difficult to predict treatment outcomes when it comes to cancer. In order to do so, researchers would need to take each of the following into account.

Tumor heterogeneity

 

As cancer grows, tumor heterogeneity tends to increase, which means the tumor becomes more complex and contains a wider range of different cell types. As a result, it becomes more difficult to treat cancer as it progresses; the more complex it becomes, the more cancer confounds oncologists and evades treatment plans. 

Tan Ince, MD, Ph.D., now Chief of Pathology at Cornell-Weill NewYork-Presbyterian Brooklyn Methodist Hospital, wasn’t satisfied with the existing ways of culturing tumor cells in the pathology lab to screen drugs against patient samples. While working at Brigham and Women’s as a pathologist and serving at Robert Weinberg’s (Ph.D.) Laboratory at MIT’s Whitehead Institute, Dr. Ince challenged this model on grounds that it didn’t accurately account for tumor heterogeneity or the dynamic nature of cancer as tumors grow.

Ince’s work helped the Weinberg lab identify and openly challenge the screening of drugs using outdated laboratory procedures for culturing cells that were developed over 60 years ago. Dr. Weinberg also rightly points out in his lectures and papers, that “mice aren’t people” and we should stop selecting drugs based on any models that don’t accurately reflect the human cancer from a patient. 

In one of his papers on ovarian cancer, Ince also developed a media that can be used to grow ovarian cancer cells in a lab while retaining the signature of the tumor or cancer that is in the patient. The media Ince developed is available to all researchers around the world today, so no laboratory should be using old methods that are not as effective. Using Ince’s media, researchers can grow ovarian cancer cells and test drugs against a true patient sample to see which combination of drugs will really work for treating the cancer as it exists in the patient’s body.

Genetic heterogeneity

 

Even the same type of cancer can affect two different patients in very different ways. This is because genetic heterogeneity is just as important to devising an effective cancer treatment as understanding tumor heterogeneity. 

For example, patients of eastern European descent are susceptible to the BRCA1 and BRCA2 genetic mutations, which could lead to the development of breast cancer and ovarian cancer. Treating these patients, then, would likely require different drug formulations than treating breast cancer or ovarian cancer patients who have a sub-Saharan African genetic background, for example, as Relling has shown in adolescents – the same is true in older patients as well. 

A good example of how even newly approved drugs suddenly stop working – or how the patient develops resistance to treatment – is found in the newly developed PARP inhibitors that were specifically designed for the BRCA1 and BRCA2 patients. These PARP inhibitors work remarkably well – until they don’t. Dr. Stephen Taylor from the University of Manchester has shown that PARP inhibitors and PARG inhibitors can work together effectively in certain ovarian cancer patient populations of BRCA1 and BRCA2 patient sets

But in order to know when they will be effective, oncologists and researchers must be able to predict treatment outcomes based on all the factors tumor heterogeneity, all the factors that go into genetic heterogeneity, and all the unique lifestyle and environmental factors that influence each individual patient. 

It’s just too much information to contextualize — until now. At Predictive, we bring the patient into the very heart of drug discovery and development.

Using artificial intelligence and machine learning to improve cancer treatments

 

The issue with cancer research historically is that it simply isn’t feasible, even for teams of experts, to possibly account for the many factors that influence how a tumor develops and grows in a particular patient and then account for which drug formulations will best treat it. That’s because the human mind can only handle so much stimuli.

Machine learning and artificial intelligence can process information so many orders of magnitude faster than human beings that it can complete countless scenarios, predicting cancer treatment outcomes with various different drug formulations, before a team of human experts has played out even a single scenario. And it can do that around the clock, 24/7/365, getting sharper and smarter as it goes. AI can improve cancer research by rapidly considering more factors about the cancer, the patient, and the treatment than humanly possible.

That’s precisely what Predictive Oncology is doing with its team at Helomics, applying three proprietary machine learning algorithms to a massive database of more than 150,000 de-identified patients, 131 types of tumors, and 30 different types of cancers. These algorithms — known as CoRETM, PeDALTM, and TruTumor— are able to analyze all this data to determine: 

  1. the top optimal drug formulations

     

  2. for the individual patient based on their genetic background and lifestyle

     

  3. based on the type of cancer and heterogeneous make-up of the tumor in its current stage. 

Armed with this information, sussed out through millions of scenarios analyzed by the AI, pharmaceutical companies would no longer have to waste time and resources on a wild goose chase developing drug formulations that were never going to pass human clinical trials in the first place. Instead, the targeted development of safe and effective drug formulations for specific types of cancer in clearly identified patient populations means a faster discovery process, streamlined drug development, and a clear path to U.S. Food and Drug Administration (FDA) approval. 

AI’s lifesaving potential and remaking the healthcare industry

 

AI and healthcare are a natural fit, enabling oncologists and pharmaceutical manufacturers to create more effective treatment plans with more useful drug formulations. But it’s not only the cancer research space that AI is set to disrupt — machine learning algorithms and their ability to contextualize immense troves of patient data are poised to remake the healthcare industry as a whole. 

Market research projections from industry analysts at Reports and Data anticipate that healthcare AI will grow to $61.59 billion in value by 2027, a compound annual growth rate (CAGR) of 43.6%. And we’ve only scratched the surface of what AI can do for human health and wellness. The lives that will be saved and the value that will be created thanks to these technologies and the novel approaches to healthcare research they enable will be immeasurable. And with the dawn of the AI-powered healthcare future, there also comes hope for a day when we finally eliminate cancer.

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Lawrence J. DeLucas, Ph.D

SVP, OPERATIONS,
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. ”

Education
  • 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.”

     

     

    Education

    Medical College of Ohio
    Doctor of Medicine

    Baldwin-Wallace University
    BS, Biology

    Richard Gabriel, BS, MBA

    SVP, RESEARCH & DEVELOPMENT
    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. ”

     

     

    Education
    Suffolk University
    Executive MBA Program

    Ohio Dominican College
    BS, Chemistry

    Ohio State University
    Microbiology and Virology

    University of Cincinnati
    Associates Degree, Liberal Arts

    Mark A Collins, Ph.D

    SCIENTIFIC/CUSTOMER DEVELOPMENT
    Predictive Oncology
    Chief Technical Officer, Helomics
    At Predictive Oncology

    Mark is currently Chief Technical Officer at Predictive Oncology. Using the power of AI, Mark is responsible for leveraging Helomics’ vast repository of physical and digital tumor samples, to build multi-omic predictive models of tumor drug response and outcome. Such models can be applied to the discovery of new targeted therapies for cancer as well as used in clinical decision support to help oncologists individualize  treatment.

    Before Predictive Oncology

    Dr. Mark Collins embarked on a career in the pharmaceutical industry following his postdoctoral work. Pursuing a passion for both biology and computing, Mark has held multiple executive roles in a variety of discovery, informatics and bioinformatics functions within global pharma, and founded three startup software companies in the artificial intelligence (AI) machine learning (ML) and drug discovery space. Mark relocated to the USA in 2001 to work for Cellomics (now part of Thermo Fisher Scientific), where he played a pivotal role in establishing the High-Content cell analysis market, building, and commercializing several key informatics and bioinformatics products.

    Since leaving Thermo Fisher, Mark has focused on developing and commercializing informatics solutions for clinical and translational research, specifically in the specimen tracking, ‘omics data management and NGS analysis space, through key roles at BioFortis, Global Specimen Solutions and Genedata

    “ I have been pursuing a vision since the late 1990s that AI will help deliver better patient therapies. I firmly believe at POAI we will deliver on that vision. ”

    Education
    University of Surrey, UK
    Ph.D., Microbiology

    University of Wolverhampton, UK
    Undergraduate Degree, Applied Science

    Bob Myers, BBA, MBA

    CHIEF FINANCIAL OFFICER
    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. ”

    Education

    Adelphi University
    MBA, Finance

    Hofstra University
    BBA, Public Accounting 

    J. Melville (“Mel”) Engle, BS, MBA

    CHIEF EXECUTIVE OFFICER
    & CHAIRMAN OF THE BOARD
    Predictive Oncology
    At Predictive Oncology
    Mr. Engle became POAI’s CEO in 2021 and was appointed to the POAI Board of Directors in 2016. He was elected Chairman of the Board in 2020.
    Before Predictive Oncology

    Between 2012 and 2021, he was CEO of Engle Strategic Solutions, a consulting and coaching company focused on CEO issues. From 2009 to 2012, he was CEO and Chairman of Thermogenesis, a cell separation company. From 2002 to 2007, he was Regional Head/Director, North America at Merck Generics and CEO of Dey Laboratories, a respiratory company. From 1996 to 2001, he was CEO and Chairman of Anika Therapeutics, an orthobiologics company. From 1980 to 1995, he was with Allergan, Inc., an eye and skin care company, where he served as CFO, Managing Director (living in Toronto), and other positions with the firm.

    “ Eliminating cancer is our overall goal.  This is not an easy task.  We are working hard every day to make this happen, using our novel technology and talented team of employees. ”

    Education

    University of Southern California
    School of Business
    MBA, Finance

    University of Colorado Boulder
    BS, Accounting