Delivering Precision Medicine’s True Potential: Big Data, Artificial Intelligence Identify New Cancer Therapeutics

Date : 10/29/2019 @ 12:45PM
Source : NetworkNewsWire
Stock : Roche Holding (QX) (RHHBY)
Quote : 38.49  0.09 (0.23%) @ 8:59PM

Delivering Precision Medicine’s True Potential: Big Data, Artificial Intelligence Identify New Cancer Therapeutics

NetworkNewsWire Editorial Coverage: The field of precision medicine has latched upon what may well be the Holy Grail in the fight against cancer. When big data are utilized by teams of pathologists, data can be incredibly helpful, but when the right data are comprehensively analyzed by artificial intelligence (AI)-powered models, the data can be downright lifesaving.

Predictive Oncology (NASDAQ: POAI) (POAI Profile) is in an enviable position in the precision-medicine industry due to its incredibly rich data set of more than 150,000 clinically validated cases on its molecular information platform, with 30,000-plus specific to ovarian cancer. The company is leveraging this unique database through Artificial Intelligence to provide the actionable insights needed to drive pharma R&D programs and improve patient outcomes. A data asset like this typically takes at least five years to fully validate and most competitors are only in the early stages of the process. Predictive Oncology already has it. The uniqueness of its data combined with its proprietary AI platform show true disruptive potential in the field of precision medicine. Leading pharma companies in the space such as Roche Holding AG (OTCQX: RHHBY), GlaxoSmithKline (NYSE: GSK), AstraZeneca (NYSE: AZN) and Bristol-Myers Squibb (NYSE: BMY) have also shown keen interest in the promise of precision medicine and are making multibillion dollar investments in the space.

  • The precision medicine market is projected to explode to more than $96 billion within the next five years.
  • POAI has already assembled one of the largest databases of drug-response and outcome data in the world.
  • Helomics’ vast database of drug-response profiles (response-ome) of 150,000 patient tumors spans 137 cancer types.

To view an infographic of this editorial, click here.

Value of Data in Precision Medicine

For some time, clinicians have been utilizing key genomic data to understand a patient’s individual tumor type in attempts to effectively prescribe therapies that will work. However, the scientific community has come to realize, due to low success rates in these applications, that genomic data itself — utilizing a just-genomics approach — doesn’t fully address the complexities of cancer and is merely scratching the surface of personalized medicine’s true potential.

The precision-medicine space has a real unmet need, with a surging demand for a multi-omic approach rather than just genomics to better understand and treat the complexities of cancer. The multi-omic approach (genome, transcriptome, epigenome, proteome, responseome and microbiome) provides researchers and clinicians the comprehensive information and interactions necessary for new drug development and treating each patient’s unique cancer in the most effective method possible. Comparatively, the multi-omic approach provides a three-dimensional, 360-degree view of the cancer, while genomics alone is just a flat, one-dimensional image.

Market Potential

Major players in the space are looking to get their hands on comprehensive, multi-omic data sets that can help them not only understand the type of cancer a patient may have but also strongly predict which therapies will be most effective in fighting each specific cancer. Unfortunately, such data is fragmented and scarce, and the initiation of such data collecting is costly and time consuming. Predictive Oncology (NASDAQ: POAI) has already assembled one of the largest databases of drug-response and outcome data in the world.

Indicating market trajectory, the precision medicine market is projected to explode to more than $96 billion within the next five years. The value of actionable data sets has steadily increased across the pharma industry, as significant acquisitions have commanded an ever-steeper price.

In January 2015, Swiss biopharma giant Roche paid $1 billion to acquire a 57% stake in molecular information developer Foundation Medicine, pledging another $157 million to accelerate product development. Underscoring the importance of precision medicine and the value of molecular information on cancers, Roche acquired the remainder of Foundation Medicine in 2018 for $2.4 billion, valuing the company at over $5.3 billion. At the time of the acquisition, Foundation Medicine reported 68,000 cases on its molecular information platform.

Predictive Assets

By comparison, Predictive Oncology (NASDAQ: POAI) currently has about 150,000 cases on its molecular information platform, with more than 30,000 specific to ovarian cancer. The company’s data is highly differentiated, having both drug-response data and access to historical outcome data from patients. The value is evidenced in a joint collaborative agreement with UPMC/Magee.

The collaboration is focused on using D-CHIP(TM), an AI platform from Helomics, a POAI subsidiary, to analyze the genomic and drug-response profiles of women with ovarian cancer to determine predictive value in terms of response/nonresponse to therapy. Both parties believe that the collaboration will demonstrate the enormous value of using AI-powered, evidence-based decision making in the context of specific treatments on specific genotypes to predict clinical outcomes for this group of patients.

With ovarian cancer as its first target, Helomics intends to sequence 50% of its 30,000-plus ovarian tumors over the next nine to twelve months, generating what may be the world’s first comprehensive, actionable, multi-omic dataset for ovarian cancer.

In addition to UPMC/Magee, Predictive Oncology has established agreements with Interpace Diagnostics Group to build AI-driven models of thyroid cancer to enhance diagnosis and identify the best therapeutic options for thyroid cancer. The company also entered a collaborative research agreement with molecular imaging company ChemImage to establish the feasibility of coupling genomics to Raman spectroscopy to better determine disease progression in prostate cancer.

Helomics also participated in the landmark 100,000 Genomes Project, a UK-government project that is sequencing whole genomes from National Health Service patients. The project is focusing on rare and infectious diseases, along with common types of cancer. The 100,00 Genomes Project featured nine major pharmaceutical companies and only one molecular information company — Predictive Oncology.

Standing Out

What sets Predictive Oncology apart in the quest for actionable cancer intelligence is that PAOI’s data assets are already in place, with data profiles dating back to 2003. By contrast, companies beginning to collect and analyze data must wait to discover how patients’ tumors will initially respond to prescribed therapies and to evaluate patient outcomes, a process that takes approximately five years. In short, POAI is on an execution trajectory not a developmental plan. By coupling outcome data with multi-omic data, POAI is creating what may be the most comprehensive, actionable dataset on ovarian cancer in the world. These actionable insights are imperative for pharmaceutical research and development programs and, most importantly, improving outcomes for the cancer patients of today and tomorrow.

Considering Roche’s $3.4 billion investment in Foundation Medicine based on the value of its molecular information, Predictive Oncology exhibits strong market potential. With a current market capitalization of only about $14 million, there should be an opportunity somewhere between here and the $3.4 billion Roche invested.

Today, Helomics’ vast database of drug-response profiles (response-ome) of 150,000 patient tumors spans 137 cancer types—a depth and breadth of data that many industry competitors only wish they could obtain. When artificial intelligence is utilized in predictive models to analyze this data, the model’s efficacy becomes more fine-tuned in congruence with such a wealth of data. Much like the search engines engineered by Google and Amazon, the more information about a patient that is fed into a machine, the better it is at predicting outcomes for that patient.

That’s the promise of precision medicine, being able to develop drugs and tailor therapeutic treatments to each individual’s specific cancer, providing the best possible outcomes. Predictive Oncology is at the vanguard of delivering the actionable intelligence required to bring the promise of precision medicine to reality.

The race to develop actionable intelligence on tumors has begun, and Predictive Oncology’s five-year head start has positioned it at the head of the pack.

Pharma on the Hunt

Roche Holding AG (OTCQX: RHHBY), a global pioneer in pharmaceuticals and diagnostics focused on advancing science to improve people’s lives, has been developing medicines with the goal of redefining treatment in oncology for over 50 years. The company’s efforts are still invested in innovative treatments, including digital health software, which provides data-driven results to support life-changing decisions. Roche uses artificial intelligence and algorithms to deliver self-learning products that constantly update available data and help healthcare professionals make more timely and informed healthcare treatment decisions.

GlaxoSmithKline (NYSE: GSK), a science-led global healthcare company, is focused on developing transformational medicines to improve survival and potentially achieve cures in the field of oncology. GSK recently announced its collaboration with the University of California to establish a new Laboratory for Genetics Research (LGR). This partnership aims to accelerate the development of next-generation functional genomics technologies and build on the databases GSK currently has available from human genetics.

AstraZeneca (NYSE: AZN), a global, science-led biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines, is utilizing precision medicine in the most prevalent and deadly tumor types. AZN is concentrating on biomarker-driven indications to dramatically improve five-year survival in five tumor types, including ovarian cancer and non-small cell lung cancer. Senior vice president of Precision Medicine at AstraZeneca Ruth March notes that the greatest advance of personalized healthcare in oncology has been the realization that some tumors are driven by individual genes. Discovering which genes cause certain types of tumors enables scientists to develop a medicine that’s best for that tumor, and then select patients that are best for that medicine.

Bristol-Myers Squibb (NYSE: BMY) is a global biopharmaceutical company whose mission is to discover, develop and deliver innovative medicines that help patients prevail over serious diseases. BMY aims to create individualized treatment strategies tailored to individual patients, offering the greatest possible patient benefit. BMY is partnering with companies to leverage next-generation sequencing to develop gene expression profiles for immune-oncology assets studied across a variety of cancers. BMY leadership sees this sequencing as a key component of precision medicine; since each tumor has a different biology, these biological differences can be associated with different outcomes. The company continues to gain new insights using sophisticated, proven and emerging technologies.

With very lives at stake, it’s little wonder that key players in the pharma sector have shifted focus to precision medicine, a powerhouse combination of rich, historical patient data and powerful AI platforms.

For more information on Predictive Oncology, visit Predictive Oncology Inc. (NASDAQ: POAI)

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