NetworkNewsWire
Editorial Coverage: Despite the enormous progress made in the
war against cancers, ovarian cancer has proved to be a tenacious
foe. Progress is being made, however, as AI predictive models are
being used to better target deadly ovarian cancers.
Ovarian cancer is difficult to treat and lethal, with survival
rates much lower than other cancers that affect women. Recently,
the battle against ovarian cancer has shifted strategy, and new
optimism has come to the fore. Predictive models using artificial
intelligence on large data sets of patient drug-treatment protocols
and historical outcomes are now providing actionable intelligence
for pharma to develop targeted therapeutics and for oncologists to
prescribe the best course of treatment to improve individual
patient outcomes. Predictive Oncology (NASDAQ: POAI)
(POAI
Profile) is laser focused on providing the molecular
information critically needed to improve the lives of women
stricken with ovarian cancer. The company has begun sequencing
ovarian cancers as part of its CancerQuest2020 project and is
building the largest ovarian multi-omic database in the world,
designed to speed the development of new drugs and provide better
therapeutic choices. The rest of pharma is also racing to find
solutions. Roche Holdings AG (OTCQX: RHHBY)
acquired a molecular information company, is researching new
ovarian specific drugs and is finding ways to identify the patients
who will benefit most from detailed molecular information.
GlaxoSmithKline PLC (NYSE: GSK) has developed a
long-term approach to finding new cancer treatments by focusing
attention in four key areas. AstraZeneca (NYSE:
AZN) recently announced a new first-line maintenance
treatment for advanced ovarian cancer. And Bristol-Myers
Squibb (NYSE: BMY) has entered into clinical
collaborations to evaluate drug combination therapeutic regimens
for ovarian cancers.
- Ovarian cancer has only a 46% survival rate.
- Understanding the complexities of ovarian cancers through
multi-omic sequencing delivers insights and actionable
intelligence.
- New insights speed drug development and deliver better targeted
treatments.
To view an infographic of this editorial, click here.
Ovarian Cancer Kills
Cancer is one of the most significant human challenges in our
history. It’s a worldwide scourge, responsible for one in six deaths each year. Major progress has been
achieved on multiple fronts, but the war is far from over. Although
no simple solution to the complexities of the disease exists, with
new insights and intelligence, the battle against unyielding
cancers can be won. Ovarian cancer is a formidable assailant. The
disease is the 11th most common cancer among women but is the fifth
leading cause of cancer-related death and is the deadliest of
gynecologic cancers. These numbers are nearly meaningless unless
the diseases takes someone close, such as a mother, sister, wife,
daughter or close friend. Thankfully, the dismal prognosis looks
like it may be about to change.
New Therapeutic Paradigm
There’s a paradigm shift occurring in cancer therapeutics, and
ovarian cancer patients look to be the beneficiaries. Treatment
protocols for ovarian cancer have historically consisted of a
combination of surgery and chemotherapy. However, the scientific
community has come to the realization that, given the vagaries and
complexities of a patient’s cancer, targeted therapeutics are
imperative to increase survival rates. To administer exactly the
right drug or drug combinations that give a patient the best chance
of survival requires comprehensive molecular information.
That’s why the work of Predictive
Oncology (NASDAQ: POAI) is so important. Predictive
Oncology’s subsidiary, Helomics, currently has about 150,000 cases
on its molecular information platform, 38,000 of which are specific
to ovarian cancer. This unique and valuable scientific asset places
Predictive Oncology among the leaders in providing the critical
molecular information needed for more effective patient treatments
and new drug discovery.
Leveraging this asset, Predictive Oncology, through Helomics,
entered a collaborative agreement with UPMC-Magee to establish a
data- and artificial-intelligence-driven approach to treating
ovarian cancer. This collaboration is expected to validate the
enormous value of using AI-powered decision-making for identifying
specific treatments on specific genotypes to predict clinical
outcomes for ovarian cancer patients. Better information leads to
better therapeutics and better outcomes.
Marking another company milestone in its CancerQuest 2020
project, Predictive Oncology announced just last week that Helomics has begun sequencing retrospective ovarian
cancer cases from the UPMC-Magee collaboration. Helomics is looking
at both the mutations in the tumor (genome) as well as the
expression of genes (transcriptome), in order to build a
comprehensive multi-omic picture of the tumor that can then be
brought together with Helomics’ data set of drug-response profiles
to build an AI-driven predictive model of ovarian cancer. This is
enormously important, as it will give clinicians, oncologists and
researchers unparalleled insights into exactly which drug or drug
combinations to use in ovarian cancer treatments and provide the
actionable intelligence required by pharma for new drug
development.
“We believe the combination of the rich multi-omic profile of
the tumor and clinical outcome data will allow us to build an
AI-driven model of ovarian cancer capable of predicting the tumor
drug response and patient outcome,” said Helomics CTO Dr. Mark
Collins.
Building Value
The value of these clinically validated, AI-driven predictive
models can’t be overstated. They may be used to predict the
relationship between a genomic profile of the patient’s tumor, the
drug response and the eventual outcome for that patient. This is
expected to provide clear, actionable insights for the clinician to
truly personalize each patient’s therapy. In the short term, these
models will be used together with Helomics’ PDx tumor-profiling
platform in revenue-generating partnerships with pharma companies
to develop new targeted therapies and to select patents for
clinical trials and in translational research projects. In
translational research projects, the model is used to dramatically
reduce the amount of experimental work by performing experiments
“in-silico,” or inside a computer. The model will then make
recommendations that Helomics can test in its CLIA laboratory.
Today Helomics has drug-response profiles and samples of over
38,000 ovarian tumors that, when sequenced, would be the largest
ovarian multi-omic database in the world. This allows Helomics to
build AI-driven predictive models of considerable scientific and
commercial value. With the company’s first predictive model
targeted for completion in early 2020, Helomics plans to have an
initial pilot with pharma using its AI predictive models to look
for new drugs/biomarkers for ovarian cancer.
In addition, Helomics has another 120,000 tumors with
drug-response data across 137 cancer types that include lung,
breast, pancreatic, colon and head and neck. The company intends to
continue moving forward in sequencing all 120,000 tumors and build
out predictive models in these additional disease categories. Once
all tumors are sequenced, Helomics will have the largest
pan-cancer, multi-omic database with drug responses in the market.
Helomics has initiated its outreach for lung-cancer outcome data
and looks to ramp up its efforts in the first quarter 2020 to
develop AI models to predict clinical outcomes for lung cancer from
genomic, drug response and outcome data. The company plans on
integrating that data along with its drug responses to have an
initial pilot in lung cancer with pharma in late-second quarter
2020.
The Opportunity
Market comparables are difficult to find since potential
competitors are privately held. The nearest comparable is
Foundation Medicine, which has been acquired by Swiss biopharma
giant, Roche. Roche paid $1 billion to acquire a 57% stake in
Foundation Medicine in January 2015. At the time of the
acquisition, Foundation Medicine reported 68,000 cases on its
molecular information platform. Underscoring the importance of
precision medicine and the value of molecular information on
cancers, Roche acquired the
remainder of Foundation Medicine last year for $2.4 billion,
valuing the company at over $5.3 billion.
By comparison, Predictive Oncology’s molecular information
platform currently has 150,000 cases with 38,000 of these specific
to ovarian cancer. POAI is rapidly building the world’s largest
ovarian multi-omic database and expects the initial model developed
with UPMC-Magee to be commercialized with pharma early next year.
The company then intends to sequence the remaining 120,000 cases to
create what will become the largest pan-cancer, multi-omic database
with drug response in the market.
Strong industry demand and large unmet medical need indicate
that Predictive Oncology’s assets may be grossly undervalued. As
PAOI continues to execute on its strategy of validation and
commercialization, it wouldn’t be surprising to see the company
soar in value.
Pharma
Predictive Oncology isn’t the only company savvy enough to see
the opportunity.
One of the first companies to offer targeted treatments based on
comprehensive molecular information was Roche Holdings AG
(OTCQX: RHHBY). The world’s largest biotech company, Roche
has put huge efforts into cancer treatment, making it a global
leader in this field. Those efforts have paid off in more effective
therapies. A large part of this comes in the form of new drugs, an
area where Roche looks to make breakthroughs. The company has
invested substantial resources into finding ways to target its
treatments for the people who will most benefit from them.
British drug giant GlaxoSmithKline PLC (NYSE:
GSK) has made cancer treatment one of its main areas of
focus. It takes years to develop new treatments, so the company has
developed a long-term strategic
approach to R&D in which it identifies novel targets,
mechanisms and potential treatments into which it can channel
resources. This concerted effort has resulted in four areas of
focus for battling cancer: using the immune system, engineering
human T-cells, affecting how DNA is directed by the epigenome, and
treatments that work by targeting the cancer in two ways at
once.
AstraZeneca (NYSE: AZN) has used its proximity
to some of the world’s finest minds to become a cancer-fighting
powerhouse. The company recently announced successful trials using
Lynparza to battle ovarian cancer, with indications of better
results than chemotherapy in specific advanced forms of the cancer.
The same drug has shown signs of effectiveness in
prostate cancer.
Bristol-Myers Squibb (NYSE: BMY) has also seen
success in recent clinical trials. These often explore not just a
single drug but a combination of treatments, as in the company’s
use of Opdivo and Yervoy together with
chemotherapy to tackle non-small cell lung cancer, a treatment
which has proven more effective than chemotherapy alone. The
European Commission has recently approved the use of
Opdivo in treating specific melanomas, allowing another pool of
patients access to more effective treatment.
As companies dedicate resources and work to win the war against
ovarian cancer, companies wielding powerful data combined with
AI-driven analytics appear well positioned to lead the pack.
For more information on Predictive Oncology,
visit Predictive
Oncology (NASDAQ: POAI)
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