Predictive Oncology
(Nasdaq: POAI), a
science-driven company leveraging its proprietary artificial
intelligence and machine learning capabilities to accelerate
oncologic drug discovery and enable drug development, today issued
the following letter to shareholders:
Dear Shareholders and Stakeholders,
As all of you know, on November 1, 2022, I had
the privilege of being asked to serve as Chief Executive Officer of
Predictive Oncology Inc. It is a responsibility that I take very
seriously, and a commitment that I made without the slightest
reservation. Predictive Oncology is a company that I believe in,
with a mission that is achievable, and a vision that is honorable.
That mission is to expedite oncologic drug discovery, enable drug
development and that vision is to bring hope to cancer patients
waiting for therapies that might improve or extend their lives
faster than currently thought possible.
As you also know, we began this journey under
less-than-optimal circumstances: management was in transition,
milestones had been delayed, the stock price had dipped below
$0.24, and the company was deficient. While disheartening, to be
sure, the Company has managed to weather the deleterious effect of
intensely volatile capital markets and the still-lingering impact
of a global pandemic. We have not only survived these external
pressures, but have made significant progress with respect to
validating our commercial platform and publishing our proof of
concept.
As frustrating as this process has been,
however, the Company is now able to focus all of its energy and
resources on conducting transactions with biopharmaceutical
partners and driving adoption of our proprietary PEDAL™ platform.
While we believe that PEDAL is the drug discovery engine that will
ultimately drive the future growth of the Company, it is the
synergy and interoperability of PEDAL, in concert with the
Company’s foundational assets of a CLIA laboratory, biorepository
of tumor samples and GMP facility that will transform our business.
At the center of these developments and activities is a highly
specialized team of world class scientists whose collective
intellectual capital is invaluable.
Lastly, it is important for me to say that, even
during the silence that has permeated this difficult transition,
one must appreciate the fact that all of the progress that has been
made during the past few months has only been possible because of
the significant and sustained investment in this Company. While it
may not be immediately obvious, I believe that the results of this
investment will become self-evident. While we may have been slowed
by circumstance, we have never given up on the Company, the
shareholders nor ourselves. I believe that Predictive Oncology will
ultimately succeed, not only because of the ongoing support of our
shareholders, stakeholders and customers, but because of the
unflinching commitment of our Board of Directors, Senior Management
and the entire team of professionals at Predictive Oncology.
AchievementsBeginning in
November, if not several months before, a concerted effort has been
made to completely rebrand and reposition Predictive Oncology as a
science-driven company utilizing proprietary artificial
intelligence (AI) to accelerate drug discovery and enable drug
development.
As we continue to move from R&D through
commercialization, we have pivoted from an ‘umbrella’ organization,
under which multiple business units operated independently, to a
singular Company providing highly specialized service offerings
along the entire continuum of drug discovery through drug
development. We have consolidated infrastructure, merged assets,
reassigned personnel and gained domain expertise, thereby creating
operational efficiencies and lowering overhead. We are not
retracting; we are positioning ourselves for future growth.
In the process of this consolidation and
reassessment of all Company assets and core competencies, we have
identified currently existing opportunities which we believe will
significantly broaden our intellectual property portfolio. This
includes the expansion of our extensive biobank of 150,000 tumor
samples, the digitization of an historic library of nearly 200,000
pathology slides, the further development of ongoing inventions and
emerging co-development opportunities with strategic partners.
We believe that the biobank itself, as well as
the slide library, which can be used for both clinical assessment
and drug discovery, each has significant value that is not
reflected on the company’s balance sheet or in the market value of
our common stock. The biobank has been internally and externally
assessed at approximately $435 million and the slide library is
currently being appraised for purposes of valuation and
monetization.
With respect to potential strategic partnerships
moving forward, and specifically with regarding the recently
announced collaboration with Cvergenx, Inc., the intent is to
leverage Predictive Oncology’s artificial intelligence drug
discovery engine (PEDAL) and machine learning capabilities (CORE™)
against the Cvergenx precision genomics radiation therapy platform
(pGRT™). In so doing, we now have the ability to optimize
radiotherapy (RT) in a way that may lead to the discovery of
medicinal radiosensitizers and radioprotectors and, potentially, to
the repurposing of existing compounds or the development of an
entirely new class of drugs.
In addition to launching PEDAL as a commercial
platform, the Company has also unveiled an initiative targeting
top-tier institutions in the academic and oncology research
community with whom the Company would like to partner. This program
— Accelerating Compound Exploration (ACE) — aims to assist academic
drug development groups and technology transfer offices in either
accelerating the data generation needed to bring a drug compound to
market, or to reinvigorate drug compounds that may not have
sufficient traction to have reached the clinic. In return, the
Company gains access to novel compounds and molecular data to
investigate and model.
The Company As a science-driven
company at the forefront of oncology drug discovery, Predictive
Oncology provides a highly precise suite of solutions for the
biopharma industry. By combining fundamental scientific rigor and a
pioneering approach to the utilization of artificial intelligence
(AI) and machine learning (ML) techniques, the Company has
accelerated and refined the ability to identify or validate target
molecules that could successfully advance along the drug
development continuum. This proprietary PEDAL platform is able to
confidently predict optimal drug/tumor combinations by introducing
human diversity earlier into the pre-clinical discovery process,
enabling drug developers to determine, with a high degree of
confidence, whether or not a compound will elicit a response in a
particular tumor type and, if so, increase its probability of
success in clinical trials. Predictive Oncology’s expanded service
offerings also include tumor models and biologics development at
our CLIA certified wet lab, with formulation design and solubility
testing in our GMP facility.
Predictive Oncology also operates a medical
device and supplies segment, Skyline, which provides the STREAMWAY®
System, a wall-mounted fully automated waste management system,
which virtually eliminates staff exposure to blood, irrigation
fluid, and other infectious fluids found in the healthcare
environment.
The Platform The PEDAL platform
relies on a unique component that no other AI drug discovery
platform currently has: access to a proprietary biobank of tumor
specific tissues consisting of more than 150,000 real-world
longitudinal samples and drug response data which have been
processed, analyzed and compiled over the past 15 years. This
biobank is the largest privately-owned tissue repository of its
kind in the world. The Company is able to utilize this historical
data, as well as query publicly available datasets of drug and
tissue features, to confidently create predictive models of drug
response involving hundreds of diverse tumor samples against
hundreds of drug compounds very early in the drug discovery
process.
The Company’s ability to test these predictive
models in a CLIA-certified wet lab environment should not be
underestimated. The scientific domain expertise, intellectual
capital and physical plant itself represent a measurable
competitive advantage over other companies that are only able to
conduct in silico testing or immortalized cell-line
experimentation. Moreover, the passage of the FDA Modernization Act
2.0, which allows new drug candidates to bypass animal testing
using computer modeling, represents a significant competitive
advantage for Predictive Oncology. The ability to seize upon this
promising opportunity is achievable because of the unique
computational capabilities of our PEDAL platform.
At the center of the PEDAL platform is the
Computational Research Engine (CORE), the underlying machine
learning technology developed at Carnegie Mellon University to
which Predictive Oncology holds world-wide exclusive rights. CORE
uses active learning to iteratively direct experimentation to
improve its predictive models. CORE utilizes a
polypharmacological/polygenomic approach that constructs a large
set of predictive models and selects the optimal pairing of data
and algorithms using a comprehensive machine learning methodology.
The more recently developed CORE Portal is a customer-centric
graphical interface that enables the visualization of PEDAL
campaigns, displays computational interactions and provides
reports.
Market Conditions* The rapidly
growing global AI drug discovery market size was valued at USD 1.1
billion in 2022 and is expected to increase at a compound annual
growth rate (CAGR) of 29.6% from 2023 to 2030 to nearly $7 billion.
The growing demand for the discovery and development of novel drug
therapies and increasing manufacturing capacities of the life
science industry are driving the demand for AI solutions in the
drug discovery processes. Manufacturers in the life science
industry constantly focus on replenishing their product pipelines,
driven in part by hugely successful drugs losing patent protection.
In addition, momentum is growing with respect to the number of
public-private partnerships that are furthering the adoption of
AI-powered solutions in drug discovery and development processes
are driving the market.
Drug discovery and development is a
cost-intensive and time-consuming process. On average, it takes ten
years and costs $2.6 billion to discover and develop a novel drug
therapy. Most therapeutic candidates are eliminated within the
initial phases of the development process, specifically during
preclinical testing and phase 1 clinical trials. This narrowing
development testing funnel directly contributes to the high costs
and extended timelines required to facilitate this process. The
adoption of AI solutions in the clinical trial process eliminates
possible obstacles, reduces clinical trial cycle time, and
increases the productivity and accuracy of the clinical trial
process. Therefore, the adoption of these advanced AI solutions in
drug discovery processes is gaining popularity amongst many life
science industry stakeholders.
According to Clinical Trials Arena data
estimates in 2021, the strategic collaborations and partnerships
between major AI-based drug discovery companies and pharmaceutical
companies increased from four partnerships in 2015 to 27
partnerships in 2020.
Digitalization in the biomedical and clinical
research space is clearing a path for the application of artificial
intelligence solutions. The range and depth of datasets generated
by the drug discovery processes, such as molecule screening and
preclinical studies, is hastening the adoption of AI-powered
solutions. Moreover, the Covid-19 pandemic dramatically changed the
perception toward clinical trials and increased the penetration and
utilization of AI solutions. Top-tier pharmaceutical companies such
as Pfizer, Novartis, Bayer, Sanofi, and Johnson & Johnson are
all collaborating with AI-based drug discovery solutions
providers.
Amongst the different phases of drug
development, preclinical testing is associated with the highest
failure rate, and is therefore extremely costly to biopharma
companies. Through the adoption of AI solutions, the preclinical
testing phase can be optimized to minimize costs. AI-based models
are implemented to accurately analyze human physiological responses
and eliminate experimental costs. Stringent regulations pertaining
to clinical trial studies laid down by regulatory authorities
across the globe are anticipated to drive the demand for AI
solutions in drug discovery processes. At the same time, government
health authorities in both developed and emerging economies are
implementing favorable initiatives to increase the penetration of
AI solutions and increase the number of active and ongoing clinical
trials.
*(Artificial Intelligence In Drug Discovery
Market Size, Share & Trends Analysis Report By Application
(Drug Optimization & Repurposing, Preclinical Testing), By
Therapeutic Area, By Region, And Segment Forecasts, 2023 –
2030).
Financial Overview Balance
Sheet: Predictive Oncology holds a strong cash position providing
approximately 18 months of liquidity and is not currently in need
of additional funding. The cash balance is further supported by a
large warrant position, the exercise of which may represent an
additional source of capital, and combined with the anticipation of
increased revenue over the next 2 -3 years, we believe that this
cash position can be managed and maintained. Other than normal
liabilities, the Company has no debt and maintains a strong equity
balance.
NASDAQ Deficiency: In May 2022, Predictive
Oncology received a price per share deficiency notification. The
Company filed an extension to remedy that deficiency in November
2022. The Company now has until May 8, 2023 to attain a minimum $1
trading price per share over ten consecutive trading days. The
process of drafting proxies, notifying investors, holding a special
shareholder meeting and filing with the SEC is lengthy and
proscribed. To manage the notification requirements regarding a
potential reverse stock split, the Company must be prepared to act
as early as mid-March in order to comply with those reporting
requirements.
If, at any time during this process, the
Company achieves compliance with Nasdaq’s minimum bid price
requirement prior to effecting a reverse stock split, there would
be no reason to proceed and, instead, the Company would terminate
the process.
Stock Buy Back: The Company’s Board of Directors
believes that the Company value and prospects are not accurately
reflected in the trading price of its common stock, and may
consider repurchasing shares of its common stock when it is able
and advisable to do so in compliance with securities laws. Based on
our schedule for filing periodic reports that publicly report our
financial condition and results of operations, and specifically
with respect to the ongoing Blackout Period, the Company does not
expect to be in a position to consider share repurchases until
mid-May 2023.
Plans and Measures The Senior
Management and Board of Directors of Predictive Oncology have been
entirely focused on addressing the most critical issues facing the
Company over the past few months: compliance with Nasdaq’s listing
requirements, stabilizing the Company’s equity, restoring investor
confidence, negotiating agreements and executing new customer
contracts.
Throughout this entire process, Management has
endeavored to be completely transparent and has maintained open
lines of communication with shareholders, brokers and potential new
investors. We have responded, and continue to respond, to all
emails, telephone calls and other requests for information, and we
have proactively reached out to new investors and have participated
in multiple investor and biopharma conferences. Our emphasis has
been, and will continue to be, on closing deals, driving adoption
of the PEDAL platform and satisfying existing contracts. Our
proposals, negotiations and engagements range from fee-for-service,
upfront compensation, short-term milestone payments and long-term
royalty fees. Opportunities currently in the pipeline include
national and international biopharmaceutical, biologics,
therapeutics and cancer research organizations, as well as
government agencies.
We will continue to pursue every opportunity to
reach and maintain Nasdaq compliance, expedite sales efforts, close
on contracts and improve shareholder value.
Acknowledgements It is
important for me to reiterate and acknowledge that virtually all of
the progress that has been made during the past few months was only
possible because of the significant investment that has been made
in this Company. It is my sincere belief that this Company will
succeed, not only because of the ongoing support of our
shareholders, stakeholders and customers, but because of the
unflinching commitment of our Board of Directors, Senior Management
and the entire team of professionals at Predictive Oncology. I look
forward to keeping you apprised of our continued progress, and I am
optimistic for what the future holds for our company.
Respectfully,
Raymond F. VennareChief Executive
Officer
About Predictive Oncology
Inc.As a science-driven company on the leading edge of
oncology drug discovery, Predictive Oncology (NASDAQ: POAI) offers
an unrivaled suite of solutions for the biopharma industry. Through
the integration of scientific rigor and machine learning, the
company has developed the ability to advance molecules into
medicine more confidently by introducing human diversity earlier
into the discovery process with the pairing of artificial
intelligence and the world’s largest privately held biobank of over
150K tumor samples. Predictive Oncology’s solutions additionally
include tumor models, biologics development, formulation design, a
GMP facility, a CLIA laboratory and substantial scientific domain
expertise.
Forward-Looking StatementsCertain matters
discussed in this release contain forward-looking statements. These
forward-looking statements reflect our current expectations and
projections about future events and are subject to substantial
risks, uncertainties and assumptions about our operations and the
investments we make. All statements, other than statements of
historical facts, included in this press release regarding our
strategy, future operations, future financial position, future
revenue and financial performance, projected costs, prospects,
plans and objectives of management are forward-looking statements.
The words “anticipate,” “believe,” “estimate,” “expect,” “intend,”
“may,” “plan,” “would,” “target” and similar expressions are
intended to identify forward-looking statements, although not all
forward-looking statements contain these identifying words. Our
actual future performance may materially differ from that
contemplated by the forward-looking statements as a result of a
variety of factors including, among other things, factors discussed
under the heading “Risk Factors” in our filings with the SEC.
Except as expressly required by law, the Company disclaims any
intent or obligation to update these forward-looking
statements.
Investor Relations Contact
Bob Myers, CFOPredictive Oncology,
Inc.bmyers@predictive-oncology.com
A photo accompanying this announcement is available at
https://www.globenewswire.com/NewsRoom/AttachmentNg/0618c6d3-202c-4951-b52c-9049a5211041
Grafico Azioni Predictive Oncology (NASDAQ:POAI)
Storico
Da Gen 2025 a Feb 2025
Grafico Azioni Predictive Oncology (NASDAQ:POAI)
Storico
Da Feb 2024 a Feb 2025