Predictive Oncology Reports Positive Results Utilizing Artificial Intelligence for Drug Repurposing
Predictive Oncology (NASDAQ: POAI) reported successful results in its drug repurposing initiative using artificial intelligence. The company identified several abandoned or discontinued pharmaceutical drugs for potential repurposing in cancer treatment, particularly for ovarian, colon, and breast cancer.
Using its proprietary AI and machine learning platform, combined with its biobank of primary tumor samples and drug response data, POAI's system made 964 confident predictions from just 92 laboratory experiments, covering 79% of all possible experiments. This eliminated approximately 18 months of wet lab testing and identified two drugs that outperformed a standard colon cancer treatment.
The company evaluated six specific drug candidates, including inhibitors targeting Akt, Aurora A, PI3Kα, HDAC1/3, VEGFR2/KDR, and PARP1/2. The drug repurposing market is projected to grow from $32.1 billion in 2023 to $51.8 billion by 2033, representing a 4.5% CAGR.
Predictive Oncology (NASDAQ: POAI) ha riportato risultati positivi nella sua iniziativa di riposizionamento dei farmaci utilizzando l'intelligenza artificiale. L'azienda ha identificato diversi farmaci farmaceutici abbandonati o interrotti per un potenziale riposizionamento nel trattamento del cancro, in particolare per il cancro ovarico, del colon e della mammella.
Utilizzando la sua piattaforma proprietaria di intelligenza artificiale e apprendimento automatico, combinata con la sua biobanca di campioni tumorali primari e dati di risposta ai farmaci, il sistema di POAI ha effettuato 964 previsioni certe da soli 92 esperimenti di laboratorio, coprendo il 79% di tutti gli esperimenti possibili. Questo ha eliminato circa 18 mesi di test in laboratorio e ha identificato due farmaci che hanno superato un trattamento standard per il cancro del colon.
L'azienda ha valutato sei specifici candidati farmaci, inclusi inibitori che prendono di mira Akt, Aurora A, PI3Kα, HDAC1/3, VEGFR2/KDR e PARP1/2. Si prevede che il mercato del riposizionamento dei farmaci crescerà da 32,1 miliardi di dollari nel 2023 a 51,8 miliardi di dollari entro il 2033, rappresentando un CAGR del 4,5%.
Predictive Oncology (NASDAQ: POAI) informó sobre resultados exitosos en su iniciativa de reposicionamiento de fármacos utilizando inteligencia artificial. La empresa identificó varios medicamentos farmacéuticos abandonados o descontinuados para un posible reposicionamiento en el tratamiento del cáncer, particularmente para el cáncer de ovario, colon y mama.
Usando su plataforma propia de inteligencia artificial y aprendizaje automático, combinada con su biobanco de muestras de tumores primarios y datos de respuesta a medicamentos, el sistema de POAI realizó 964 predicciones confiables a partir de solo 92 experimentos de laboratorio, cubriendo el 79% de todos los experimentos posibles. Esto eliminó aproximadamente 18 meses de pruebas en laboratorio e identificó dos fármacos que superaron un tratamiento estándar para el cáncer de colon.
La empresa evaluó seis candidatos a fármacos específicos, incluidos inhibidores que apuntan a Akt, Aurora A, PI3Kα, HDAC1/3, VEGFR2/KDR y PARP1/2. Se proyecta que el mercado de reposicionamiento de fármacos crecerá de 32.1 mil millones de dólares en 2023 a 51.8 mil millones de dólares para 2033, representando un CAGR del 4.5%.
Predictive Oncology (NASDAQ: POAI)는 인공지능을 활용한 약물 재배치 이니셔티브에서 성공적인 결과를 보고했습니다. 이 회사는 난소암, 대장암 및 유방암 치료에 대한 잠재적인 재배치를 위해 여러 개의 버려지거나 중단된 제약 약물을 확인했습니다.
자체 AI 및 머신러닝 플랫폼과 주요 종양 샘플 및 약물 반응 데이터의 바이오뱅크를 결합하여 POAI의 시스템은 단 92개의 실험에서 964개의 신뢰성 있는 예측을 수행했으며, 이는 가능한 모든 실험의 79%를 포함합니다. 이는 약 18개월의 실험실 테스트 시간을 단축시키고 표준 대장암 치료를 초과하는 두 가지 약물을 확인했습니다.
회사는 Akt, Aurora A, PI3Kα, HDAC1/3, VEGFR2/KDR 및 PARP1/2를 타겟으로 하는 억제제를 포함한 여섯 가지 특정 약물 후보를 평가했습니다. 약물 재배치 시장은 2023년 321억 달러에서 2033년 518억 달러로 성장할 것으로 예상되며, 이는 연평균 4.5%의 성장률을 나타냅니다.
Predictive Oncology (NASDAQ: POAI) a rapporté des résultats positifs dans son initiative de repositionnement de médicaments utilisant l'intelligence artificielle. L'entreprise a identifié plusieurs médicaments pharmaceutiques abandonnés ou interrompus pour un potentiel repositionnement dans le traitement du cancer, en particulier pour le cancer de l'ovaire, du côlon et du sein.
En utilisant sa plateforme propriétaire d'IA et d'apprentissage automatique, combinée à sa biobanque d'échantillons de tumeurs primaires et de données de réponse aux médicaments, le système de POAI a effectué 964 prédictions fiables à partir de seulement 92 expériences de laboratoire, couvrant 79 % de toutes les expériences possibles. Cela a permis d'éliminer environ 18 mois de tests en laboratoire et d'identifier deux médicaments qui ont surpassé un traitement standard du cancer du côlon.
L'entreprise a évalué six candidats médicamenteux spécifiques, y compris des inhibiteurs ciblant Akt, Aurora A, PI3Kα, HDAC1/3, VEGFR2/KDR et PARP1/2. Le marché du repositionnement de médicaments devrait passer de 32,1 milliards de dollars en 2023 à 51,8 milliards de dollars d'ici 2033, représentant un TCAC de 4,5 %.
Predictive Oncology (NASDAQ: POAI) berichtete über erfolgreiche Ergebnisse in seiner Initiative zur Wiederverwendung von Arzneimitteln unter Verwendung von künstlicher Intelligenz. Das Unternehmen identifizierte mehrere aufgegebene oder eingestellte pharmazeutische Arzneimittel für eine potenzielle Wiederverwendung in der Krebsbehandlung, insbesondere bei Eierstock-, Dickdarm- und Brustkrebs.
Mit seiner proprietären KI- und Machine-Learning-Plattform, kombiniert mit seiner Biobank von primären Tumorproben und Daten zur Arzneimittelreaktion, machte das System von POAI 964 zuverlässige Vorhersagen aus nur 92 Laborexperimenten, die 79 % aller möglichen Experimente abdeckten. Dies sparte etwa 18 Monate an Laboruntersuchungen und identifizierte zwei Arzneimittel, die eine Standardbehandlung für Dickdarmkrebs übertrafen.
Das Unternehmen bewertete sechs spezifische Arzneimittelkandidaten, einschließlich Inhibitoren, die auf Akt, Aurora A, PI3Kα, HDAC1/3, VEGFR2/KDR und PARP1/2 abzielen. Der Markt für die Wiederverwendung von Arzneimitteln wird voraussichtlich von 32,1 Milliarden US-Dollar im Jahr 2023 auf 51,8 Milliarden US-Dollar im Jahr 2033 wachsen, was einem CAGR von 4,5 % entspricht.
- AI platform successfully predicted drug efficacy with 10x efficiency, saving 18 months of testing time
- Two identified drugs outperformed standard colon cancer treatment
- Platform achieved 79% coverage of possible experiments from initial testing
- Operating in growing market projected to reach $51.8B by 2033 (4.5% CAGR)
- None.
Insights
The successful identification of repurposed drug candidates represents a potentially transformative milestone for Predictive Oncology. The company's AI platform has demonstrated remarkable efficiency by generating 964 confident predictions from just 92 laboratory experiments, potentially eliminating 18 months of traditional wet lab testing. This represents a significant competitive advantage in the drug development landscape, where time and cost efficiencies are crucial.
The selection of drug candidates, including Akt, Aurora A, and PI3Kα inhibitors, is particularly strategic. These drug classes have established safety profiles and known mechanisms of action, which could significantly reduce development risks and costs. Traditional drug development typically costs
The focus on ovarian, colon, and breast cancers is commercially astute, as these represent large market opportunities with significant unmet medical needs. The company's biobank of primary tumor samples provides a unique competitive advantage, enabling more accurate predictions of drug efficacy. The outperformance of two drug candidates against standard colon cancer treatments is particularly noteworthy, as it could attract partnership interest from major pharmaceutical companies looking to expand their oncology portfolios.
The projected growth of the drug repurposing market to
Company successfully identified several abandoned or discontinued drugs for further testing and development in ovarian and other cancer types
Creates significant business development opportunities with meaningful long-term commercial potential with large pharmaceutical companies
PITTSBURGH, Feb. 18, 2025 (GLOBE NEWSWIRE) -- Predictive Oncology Inc. (NASDAQ: POAI), a leader in AI-driven drug discovery and biologics, today provided an update highlighting new successes with its drug repurposing initiative.
Using publicly available datasets on drugs that have either been abandoned or discontinued by large pharmaceutical companies, Predictive Oncology has developed a registry of promising candidates that can potentially be repurposed for additional or alternative indications.
By utilizing its proprietary artificial intelligence and machine learning platform and leveraging its vast biobank of primary tumor samples and decades of drug response data, Predictive identified select drug candidates with promising mechanisms of action for further clinical testing with an initial focus on ovarian, colon and breast cancer and subsequently identified candidates with potential efficacy in treating colon and ovarian cancer.
“Early results show that by running our platform for just eight weeks, we were able to identify compounds for use in one or more tumor types,” said Dr. Arlette Uihlein, Senior Vice President of Translational Medicine and Drug Discovery and Medical Director at Predictive Oncology. “By precisely measuring only 92 combinations of laboratory experiments on patient tumor samples, the predictive model was capable of making an additional 964 confident predictions, covering a total of
“Our active learning AI platform enabled us to efficiently and confidently predict an additional 10x the number of measured experiments, eliminating at least 18 months of wet lab testing and identifying two drugs as having very promising results for use in one or more tumor types. Both of these drugs outperformed a known standard of care drug used to treat colon cancer,” Dr. Uihlein concluded.
Specific examples of currently abandoned or discontinued drugs that Predictive evaluated for potential efficacy include:
- Drug A: Akt Inhibitor
- Drug B: selective Aurora A Inhibitor
- Drug C: selective PI3Kα Inhibitor
- Drug D: HDAC1/3 Inhibitor
- Drug E: VEGFR2/KDR Inhibitor
- Drug F: PARP1/2 Inhibitor
Leveraging the company’s foundational proof of concept study, Predictive is also using its AI platform to identify a set of FDA-approved drugs for other cancers that show promising activity in ovarian cancer, the results of which will soon be made public.
“Encouraged by the outcome of the Magee Study and ASCO presentation, which predicted short and long-term survival of ovarian cancer patents, we made a conscious decision to proactively investigate potential candidates for drug repurposing or reuse specifically for ovarian cancer,” said Raymond Vennare, Chief Executive Officer of Predictive Oncology. “We continue to demonstrate that our high throughput screening approach using the live cell patient tumors in our biobank, coupled with our AI models, is able to identify drugs worthy of further consideration. The significance of these initial drug repurposing findings may lead to some very productive discussions with a range of potential drug development partners.”
Utilizing its artificial intelligence platform, the company believes that the ability to repurpose approved or abandoned drugs for additional indications represents a meaningful opportunity to deliver value by developing new therapies faster and cheaper than through traditional early drug discovery. A recent market report has projected that the market for repurposed drugs will grow to
About Predictive Oncology
Predictive Oncology is on the cutting edge of the rapidly growing use of artificial intelligence and machine learning to expedite early drug discovery and enable drug development for the benefit of cancer patients worldwide. The company’s scientifically validated AI platform, PEDAL, is able to predict with
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tim@lifesciadvisors.com
Forward-Looking Statements:
Certain 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, changes in management, 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.
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