Why the next drug revolution will be algorithmic

By Sergey Jakimov and Artem Trotsyuk, managing and operating partners at LongeVC

Artificial intelligence is rapidly rewriting medicine – from clinics to labs – and scientists, startups, regulators, and investors are shaping that shift together. The global healthcare AI market is projected to soar from just over $1 billion in 2016 to more than $28 billion by 2025.

The first AI-designed molecules are already in human trials, compressing timelines that once stretched a decade into just a few years. This marks a structural change in how therapies are designed and how we define patient care. A data-driven revolution is underway, and its upside is enormous.

Healthcare has felt AI’s presence in imaging, triage, and early diagnostics, but the deeper transformation is happening in labs and discovery pipelines. AI systems now predict protein folding (Demis Hassabis and John Jumper received the Nobel Prize in Chemistry 2024 for their AlphaFold2 model), map new drug targets, and propose molecular structures at a pace that traditional methods cannot match.

Where traditional discovery might take five years and hundreds of millions before a first clinical trial, AI is cutting that in half. Insilico Medicine, for example, went from target identification to a Phase I trial in about 30 months with its idiopathic pulmonary fibrosis candidate, giving proof that generative chemistry can yield clinical assets. 

AOA Dx offers another glimpse of what this transformation looks like in practice. The company is using AI to interpret complex biomarker data from blood, aiming to detect ovarian cancer at its earliest stages: when survival rates are above 90%, compared with less than 20% for late diagnoses.

In its recent trial with over 500 women, AOA’s algorithm-driven approach achieved specificity and sensitivity levels that exceeded FDA thresholds, positioning it as the first to demonstrate reliable blood-based early detection for this cancer. It’s a case study in how AI can open entirely new diagnostic frontiers, not just streamline existing processes.

For years, “personalized medicine” was more slogan than reality. Early efforts often relied on broad biomarkers or risk categories, treating patients as members of subpopulations rather than as unique individuals.

Truly individualizing therapy requires integrating vast multi-omic and real-time data streams. And this challenge was simply unfeasible with older tools.

Now, AI is providing the infrastructure to make it practical. Companies are integrating genomics, microbiome data, and digital biomarkers into algorithms that guide individual-level decisions.

A European SaaS startup, Haut.AI, is doing this in dermatology by analyzing skin phenotypes to recommend targeted interventions. The company reports its model achieves roughly 98% diagnostic accuracy across diverse skin types by analyzing more than 20 clinically relevant skin metrics, enabling finely tuned interventions rather than one-size-fits-all skincare.

Ani Biome is applying generative AI to microbiome analysis, producing supplements that aim to optimize gut health and reduce inflammation. These are early steps toward a future where therapies and preventions are tuned not to populations, but to individuals. We see it as a signal of a true shift in preventive care. 

By continuously integrating genomic, microbiome, and biomarker data, future algorithms could update each person’s health plan in real time to slow aging. That this kind of n-of-1 precision is exactly what will underpin breakthroughs in age-related disease and healthspan extension.

The capital markets are noticing the shift as well. Investment in AI-driven healthcare ventures has surged, even though the investing market stays pretty rough (make this sentence better. Pharma companies are partnering with AI labs not as experiments but as core R&D bets.

For example, Merck recently inked a $349M collaboration with Variational AI to co-design novel small molecules. As reported by Silicon Valley Bank, venture investment in healthcare AI reached $5.7B across 320+ deals in the first half of 2025, making it one of the most active subsectors.

Biopharma accounted for the majority, reflecting growing confidence that AI is not just an efficiency tool but a true source of pipeline innovation

The capital markets are also noticing the shift. Venture dollars are tilting toward AI-native plays, even amid a cautious funding environment.

As reported by Silicon Valley Bank, U.S. healthtech has seen the biggest share of the AI healthcare boom: trailing 12-month AI deal activity in healthtech has roughly doubled since 2022 and accounted for nearly a third of all healthcare investment in the first half of 2025.

Healthcare-specific AI models, pure software drug-discovery platforms, and a wave of new administrative tools have made the sector one of the most attractive categories for investors. Pharma companies are also signing AI-first partnerships: Merck recently inked a $349M collaboration with Variational AI to co-design novel small molecules, in September 2024 Novartis signed a deal with Generate:Biomedicines (up to $1B+) for AI-designed proteins.

Startups like Ani Biome, Glyphic Bio, Melio, and Valink Therapeutics are applying AI to everything from microbiome analysis to signal deconvolution and drug design, showing how machine learning is now embedded across the discovery value chain.

Better prediction reduces failed trials, saving billions while de-risking pipelines. But the deeper opportunity is strategic: AI allows small, early-stage teams to generate assets that once required the budget of Big Pharma, changing who gets to compete in therapeutics.

The implication for longevity biotech is profound: a tiny team can now explore aging-related pathways without a billion-dollar budget. By democratizing drug discovery, AI could spark a wave of startups tackling neglected geroscience targets.

This lower barrier to entry may rapidly accelerate the development of geroprotective therapies that were previously too complex or niche for larger companies.

Many commercial “anti-aging” or “AI health” products overpromise, and clinicians rightly point to bias and explainability gaps in black-box models. Regulators are starting to respond: the FDA and EMA have both issued early guidance on adaptive algorithms in healthcare. If trust is to grow, transparency and clinical validation will need to be non-negotiable. In fact, the FDA’s AI Action Plan explicitly emphasizes bias mitigation and robust validation of medical AI. Any AI-derived therapy will need the same rigorous trials and peer-reviewed evidence as a traditional drug. In practice, this means the field must police hype aggressively – promising results backed by data, not snake oil. Without clear, evidence-based validation, even groundbreaking algorithms will be viewed skeptically.

The thesis is simple: drug discovery is being redefined by algorithms, and medicine will not look the same in a decade. AI has already delivered its first clinical candidates. The question is no longer “if,” but “how fast”, and whether the industry can scale these tools responsibly.

What’s clear is that the winners in biotech and longevity will be those who learn to work with algorithms not as black boxes, but as partners in the next era of medical innovation.

C-suite agetech hires from the last 30 days

Paul Taheri — InnovAge — Chief Medical Officer

InnovAge (Nasdaq: INNV), a leading U.S. PACE provider for frail, predominantly dual-eligible seniors, has appointed Dr Paul Taheri as CMO. Taheri brings 30+ years across Yale Medicine (CEO & deputy dean for clinical affairs), University of Vermont Medical Group (president/CEO) and advisory work with WCAS. CEO Patrick Blair highlighted Taheri’s blend of clinical and operating experience to support InnovAge’s multi-state footprint and quality agenda. The role follows InnovAge’s leadership refresh after its prior CMO departed in April. Expect emphasis on clinical outcomes, compliance and center growth.

Keith Kuhn — CarePatrol (Best Life Brands) — Brand President

Best Life Brands named Keith Kuhn brand president of CarePatrol, the senior-care placement franchise. Kuhn co-founded CarePatrol’s predecessor in the 1990s and returns with 35+ years of healthcare leadership. As part of the transition, longtime leader and co-founder Becky Bongiovanni moves to an advisory role—keeping founder continuity while handing day-to-day leadership to Kuhn. The company frames the move as positioning CarePatrol to scale its advisor network and franchise operations across 230+ territories. Expect focus on franchise performance, payer/partner ties and consumer marketing.

Yan Li — Zhong Ji Longevity Science Group — Chief Executive Officer

HK-listed Zhong Ji Longevity Science Group confirmed the appointment of executive director Yan Li as CEO, effective 17 Oct, in a supplemental announcement dated 7 Nov. The filing also notes the resignation of former CEO Yan Yifan (and a board gender-diversity remedial plan by Jan 2026). Yan Li, already board chair, takes on CEO duties without additional remuneration initially, signalling a consolidation of leadership while the company navigates a transformation phase in its longevity science portfolio. Watch for governance updates and strategic resets.

Rebecca Woodcock — Belong — Chief Operating Officer

UK not-for-profit dementia specialist Belong promoted Rebecca Woodcock to COO (9 Nov). Woodcock moves up from group operations manager after two decades with the organisation, including leadership roles at Atherton and Wigan villages. She’ll oversee Belong’s dementia villages and home-care services, with an emphasis on operational excellence and CQC standards (several sites hold “Outstanding”). The move strengthens Belong’s experienced executive bench as demand for specialist dementia care and community-based models rises in the UK.

Gaurav Bagga — Emoha Eldercare — Chief Technology Officer

India’s Emoha Eldercare appointed Gaurav Bagga as CTO (reported 5 Nov). Bagga brings 15+ years in tech leadership and will drive Emoha’s digital health & safety stack for seniors—spanning remote monitoring, emergency response and engagement. The hire underscores Emoha’s push to scale a data-driven platform for at-home ageing in India’s rapidly expanding elder-care market. Expect product roadmap acceleration (apps, dashboards, analytics) and deeper integrations with clinical and non-clinical partners.

From the last 30 days, relevant to agetech and ageing health innovation

Date: 13 Oct 2025
Body: FDA (U.S.)
Topic: 510(k) IVD clearance
Product/Indication: Roche Elecsys pTau181 — primary-care blood test to help rule out Alzheimer’s amyloid
Takeaway: First FDA-cleared Alzheimer’s blood test for primary care rule-out.
Read more: Roche

Date: 24 Oct 2025
Body: NICE (UK)
Topic: Guideline surveillance (NG97)
Product/Indication: Dementia — assessment, management & support
Takeaway: Surveillance completed; no updates to NG97 at this time.
Source: NICE

Date: 31 Oct 2025
Body: CMS (U.S.)
Topic: Medicare PFS Final Rule (CPT/payment)
Product/Indication: RPM/RTM, telehealth, virtual direct supervision (2026 policy)
Takeaway: Confirms virtual direct supervision; updates RPM/RTM payment policies.
Source: cms.gov

Date: 05 Nov 2025
Body: MHRA (UK)
Topic: Device registration fees/guidance
Product/Indication: All UK medical devices (incl. custom-made; DORS)
Takeaway: From 1 Apr 2026, annual fee model replaces one-off application fee.
Source: GOV.UK

Date: 06 Nov 2025
Body: FDA (U.S.)
Topic: Advisory committee (Digital Health)
Product/Indication: AI-enabled digital mental-health devices (older adults among users)
Takeaway: DHAC met to discuss benefits/risks and oversight of AI mental-health devices.
Source: U.S. Food and Drug Administration

Date: 10 Nov 2025
Body: FDA (U.S.)
Topic: 510(k) clearance
Product/Indication: Stereotaxis GenesisX robotic magnetic navigation (cardiac EP for older adults too)
Takeaway: Clearance for compact robot may broaden access to EP procedures.
Source: ir.stereotaxis.com

Date: 10–13 Nov 2025 (agenda)
Body: EMA/CHMP (EU)
Topic: Committee agenda / oral explanations
Product/Indication: Alzheimer’s therapies (e.g., listed oral explanations during session)
Takeaway: November CHMP agenda includes neurology items with oral hearings.
Source: European Medicines Agency (EMA)

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