{"id":305832,"date":"2026-02-19T09:20:08","date_gmt":"2026-02-19T09:20:08","guid":{"rendered":"https:\/\/www.newsbeep.com\/ie\/305832\/"},"modified":"2026-02-19T09:20:08","modified_gmt":"2026-02-19T09:20:08","slug":"ai-in-drug-repurposing-cancer-survival-pledge","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ie\/305832\/","title":{"rendered":"AI in drug repurposing: Cancer survival pledge"},"content":{"rendered":"

\"AI<\/a>image: \u00a9BlackJack3D | iStock
\n Dr Shivan Sivakumar emphasises the need to rethink cancer care, advocating for the use of Artificial Intelligence (AI) in drug repurposing as a faster, cost-effective alternative to developing new therapies<\/p>\n

I\u2019ve spent much of my career in oncology wrestling with a frustrating reality that while we\u2019ve made remarkable strides in diagnosing cancer, our ability to treat it \u2013 especially in the survivorship phase \u2013 hasn\u2019t kept pace.<\/p>\n

We\u2019ve become very good at identifying specific genetic cancer variants through advanced diagnostics. Yet, cancer treatment can only target 46 of the 750 known mutations which impact the disease\u2019s progression and recurrence.<\/p>\n

This gap directly aligns with the newly published NHS 10 Year Plan, which calls for earlier diagnosis and a pipeline of affordable, personalised interventions to keep patients cancer-free.<\/p>\n

Specifically, this gap leaves patients in a vulnerable state post-treatment, often handed the outdated advice to \u2018watch and wait\u2019 for the cancer to return. It\u2019s a passive approach that fails both patients and clinicians, and I believe it\u2019s time to rethink how we address cancer care, particularly for individuals who have survived cancer.<\/p>\n

Addressing the survivorship gap: AI-driven drug repurposing for cancer recurrence prevention<\/p>\n

Artificial Intelligence<\/a> does not just have a role to play in new drug discovery and diagnostics. It has the potential to have a major impact on drug repurposing, a faster, cheaper solution that is better for patients.<\/p>\n

We need to challenge the conventional narrative that the future of cancer treatment lies solely in developing new drugs. Don\u2019t get me wrong, new therapies are vital, but they often take over a decade and billions of pounds before they\u2019re available. Meanwhile, cancer survivors are left without proactive options to prevent recurrence during a time when intervention could dramatically improve outcomes. This survivorship gap, historically underfunded compared to diagnostics and active treatment, represents our greatest opportunity to change lives. The real breakthrough isn\u2019t in chasing elusive new compounds but in leveraging AI to unlock the potential of existing, well-understood drugs to target patient-specific mutations and delay or prevent the cancer\u2019s return.<\/p>\n

Consider the scale of the problem. After surgery or chemotherapy, most cancer survivors, across nearly all cancer types, have no standard maintenance treatment. They\u2019re told to monitor for symptoms and hope for the best. This isn\u2019t just a medical oversight; it\u2019s an emotional burden, leaving patients feeling powerless when agency matters most.<\/p>\n

Using AI, it\u2019s possible to bridge the gap by analysing over 100,000 peer-reviewed research papers to identify low-cost, low-toxicity drugs already on the market that can target the full spectrum of 750 cancer driver mutations. Because these medicines are already generic, they directly support the NHS 10 Year Plan\u2019s emphasis on cost-effective innovation that reduces health inequalities. This approach isn\u2019t about replacing active treatment but about extending remission through personalised care that empowers patients beyond \u2018watching and waiting\u2019.<\/p>\n

Leveraging AI to discover multi-target drug combinations<\/p>\n

In this context, the power of AI lies in its ability to process vast datasets, including biological, clinical, and pharmacological datasets, to uncover connections humans might miss. For instance, a study<\/a> in the National Institutes of Health (NIH) database suggests that anti-inflammatory drugs may reduce the risk of disease recurrence in breast cancer patients by 42%. What AI can do is identify combinations of existing drugs that can simultaneously target multiple cancer vulnerabilities, say four or five at once, maximising impact while minimising toxicity.<\/p>\n

These aren\u2019t speculative treatments; they\u2019re based on existing evidence, repurposed for preventative care in ways that are safe, tolerable and affordable for long- term use. Unlike targeted therapies, which are often too toxic or costly for sustained application, the focus is on drugs that patients can integrate into their lives without the fear of debilitating side effects or financial ruin.<\/p>\n

This form of AI not only creates value, but it also democratises cancer care by making evidence-based interventions available to more patients sooner. It isn\u2019t about profit through exclusivity, it\u2019s about impact through accessibility.<\/p>\n

A patient-centric approach to preventing cancer recurrence with AI<\/p>\n

I\u2019m often asked how this aligns with broader trends in oncology, including diagnostics. While initiatives like the UK\u2019s funding of new blood tests for early cancer detection<\/a> \u2013 capable of identifying 12 common cancers with over 99% accuracy \u2013 are transformative, they highlight the same diagnostic-treatment mismatch I\u2019ve described. Early detection saves lives only if paired with effective interventions, yet many patients still face the survivorship gap post-treatment.<\/p>\n

Work by companies complements such diagnostic advances by ensuring that once cancer is detected or treated, patients aren\u2019t left without options. Using AI to analyse existing knowledge and focus on therapeutic repurposing to reduce the risk of recurrence is a critical next step after diagnosis. The NHS states every survivor should receive a personalised care plan; AI can support insights into daily, manageable guidance that patients can trust.<\/p>\n

The patient perspective should drive everything we do. Survivorship isn\u2019t just about surviving; it\u2019s about thriving. Imagine a breast cancer survivor with a specific mutation profile receiving a tailored care plan of repurposed drugs, backed by peer-reviewed evidence, that targets her unique recurrence risks. She\u2019s no longer passively waiting for bad news; she\u2019s actively managing her health with affordable, tolerable medications. This shift could redefine survivorship, reducing not just recurrence rates but also the psychological toll of living in limbo.<\/p>\n

Of course, challenges remain. Integrating AI-driven repurposing into clinical practice requires overcoming healthcare providers\u2019 scepticism. There\u2019s also the hurdle of regulatory acceptance and payer reimbursement for off-label drug use. Yet, the evidence is mounting \u2013 studies like those highlighted by the European Society for Medical Oncology (ESMO)<\/a> emphasise the need for high-quality survivorship care that addresses physical, psychological and recurrence risks.<\/p>\n

The AI-powered future of cancer survivorship<\/p>\n

Looking ahead, I envision a future where every cancer survivor benefits from a personalised care plan, tailored by AI to their molecular profile and grounded in existing drugs. The survivorship phase, long neglected, could become the frontier of oncology innovation, as noted in discussions<\/a> around rethinking cancer care models. If we can address all 750 cancer driver mutations through repurposing, rather than the current 46, we\u2019ll offer a comprehensive shield against cancer, not just a partial one.<\/p>\n

To get there, we need a collective shift in mindset from patients and clinicians to policymakers and the pharma industry. We must prioritise survivorship alongside early detection, recognising that the post-treatment phase offers an immediate opportunity to improve outcomes. As reports like the AACR\u2019s forecasts<\/a> suggest, AI and precision medicine are poised to advance cancer care, including through innovative therapeutic strategies. Cancer care doesn\u2019t need more waiting; it requires action, and AI-driven drug repurposing is how we deliver it.<\/p>\n

I urge the oncology community to rethink where we invest our resources and focus. Money is poured into early detection and novel therapies, yet survivorship remains an afterthought. Let\u2019s change that by harnessing AI to repurpose existing drugs, giving survivors not just hope but tangible, personalised tools to extend remission. The NHS\u2019s commitment to embed novel digital tools over the next decade is hugely welcome. We now need to make sure every early diagnosis is matched by an equally advanced survivorship strategy.<\/p>\n","protected":false},"excerpt":{"rendered":"image: \u00a9BlackJack3D | iStock Dr Shivan Sivakumar emphasises the need to rethink cancer care, advocating for the use…\n","protected":false},"author":2,"featured_media":305833,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[218,258,10818,103,61,60,140320],"class_list":["post-305832","post","type-post","status-publish","format-standard","has-post-thumbnail","category-health","tag-artificial-intelligence","tag-cancer","tag-drug-development","tag-health","tag-ie","tag-ireland","tag-oag-049-january-2026"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/305832","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/comments?post=305832"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/305832\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media\/305833"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media?parent=305832"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/categories?post=305832"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/tags?post=305832"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}