Beyond ‘one drug, one disease’: a promising signal for the future of genetic medicine

A new regulatory model is emerging for platform-based genetic medicines

The THRIVE awardee announcements have arrived shortly after the FDA’s proposed pathway for individualised genetic medicines in February 2026. The pathway recognises that conventional drug development regulatory requirements are impractical for therapies designed for one patient, or for a very small group with a rare genetic variant.

Of course, designing the therapy is only part of the problem. The harder questions are how to generate enough evidence, manage safety, satisfy regulators and make the economics work when the patient populations are so small. Together, the FDA’s thinking and ARPA-H’s investment suggest the field is meaningfully shifting from “could this ever be possible” to “what would need to be true for this to work?”.

Could platform-based genetic medicines be even more personalised than we think?

It is easy to look at today’s medicine pipeline and assume the future will mainly be off-the-shelf products for broad indications. That may still be true for much of the market. But several trends point towards a more personalised future, particularly for genetic medicines:

• Genome sequencing is becoming routine and increasingly affordable.
• Gene editing technologies are inherently programmable.
• AI is accelerating therapeutic design.
• Manufacturing systems are becoming more automated.

Combined with the fact that every patient’s genome is unique, those trends make it plausible that therapies could be developed for far smaller patient populations than pharma has historically served.

That does not mean n=1 genetic medicines are about to become routine. Major questions remain around targeting, off-target effects, clinical benefit, safety data, reimbursement and regulation. There’s also the question of whether manufacturing and quality systems can move quickly enough to support that level of customisation. Rather than applying the full clinical trial and regulatory process to every individual therapy, a platform-based approach could create a system that supports multiple treatments. This could only be possible if the ambitions that underpin programmes like THRIVE can be achieved.

Conventional manufacturing won’t cut it

If we can design, assess and approve highly tailored genetic medicines through platform-based mechanisms, the next question is, how do we make them?

The conventional manufacturing model is built around centralised, large-batch production. That works when the same product goes to many patients. It is harder to reconcile with products that change frequently and may be made in very small batches.

In simple terms, the field may eventually need something closer to a genetic medicine equivalent of a 3D printer (that being a standardised manufacturing platform capable of producing many different therapies from the same underlying infrastructure).

The long-term vision is straightforward. A patient’s genetic information is collected and analysed, the therapy payload is designed using validated tools and the formulation design is entered into an automated manufacturing platform. Then a small batch of medicine is produced, tested and released before being administered to the patient or patients.

The same infrastructure could, in principle, support repeatedly both individual patients and small groups with a shared rare genetic disorder. That still sounds futuristic, but ARPA-H is already investing in parts of the enabling infrastructure.

Enter GIVE: manufacturing for personalised medicine

THRIVE’s companion programme from ARPA-H, GIVE (Genetic Medicines and Individualised Manufacturing for Everyone), focuses directly on this manufacturing problem.

Its stated objective is to create a “multi-site, multi-product, and multi-scale biomanufacturing network with distributed manufacturing and integrated quality control capabilities for RNA-based genetic medicines”.

To me, the important point is that GIVE is not simply about decentralised manufacturing. It is about whether standardised manufacturing infrastructure can support increasingly customised products.

The business case

For now, most commercial investment will still favour broader off-the-shelf genetic medicines, as the well-trodden path is deemed less risky. Truly individualised therapies remain uncommon, and Baby KJ will probably remain an exceptional case for some time. However, the argument that personalised genetic medicines simply cannot be made into a profitable business model is looking a lot less certain.

The business case for highly tailored medicines is no longer purely theoretical. In oncology, both Moderna and BioNTech are investing heavily in personalised mRNA cancer vaccines that are individually designed around the mutations present within each patient’s tumour. Moderna’s personalised oncology platform is called Individualised Neoantigen Therapy (INT) and is part of their explicit “One Medicine for One Patient” strategy. While BioNTech was arguably one of the earliest pioneers of personalised neoantigen vaccines, with a platform called iNeST (Individualised Neoantigen Specific Immunotherapy).

Their respective programmes, developed with Merck and Genentech/Roche, use standardised sequencing, custom treatment design, and manufacturing platforms to generate bespoke RNA therapies on a patient-by-patient basis. Whilst these products target cancer rather than inherited disease, they demonstrate that some of the industry’s largest and most commercially sophisticated organisations believe personalised medicines can be manufactured, regulated and delivered at sufficient scale to create sustainable business models.

Perhaps more importantly, these programmes suggest that the economics of personalised medicine may depend less on manufacturing the same product for millions of patients and more on repeatedly manufacturing different products using the same platform. This is still to trat millions of patients, and potentially with better clinical outcomes. Of course, they are targeting the large and lucrative oncology market.

As the success of programmable genetic medicines progresses, the approach will likely also be considered for other indication groups. Oncology is well suited to the approach because everyone’s cancer is different, so customisation becomes a big advantage. Personalised medicines become attractive wherever the biological variability between patients is a major determinant of treatment success. Hence, we can expect this approach to be considered for other areas such as autoimmune disease, transplantations, and rare/ultra-rare genetic disorders.

In the case of rare & ultra-rare genetic disorders, don’t be fooled by the name. While each disorder itself is rare, many people suffer from genetic disorders. Some reports estimate that approximately 300 million people live with a rare disease, so there still represents a compelling business case. This is only if customised therapies can be designed, assessed, approved, and manufactured using a platform-approach.

The main challenges facing platform-based genetic medicines

None of this is straightforward. Scientific hurdles remain significant, including delivery to difficult-to-target tissues, editing efficiency, off-target activity, immunogenicity and clinical validation.

Even if those problems continue to improve, challenges will remain around manufacturing, quality control and regulation. That is where the FDA’s new pathways, along with the ARPA-H’s THRIVE and GIVE initiatives, become particularly interesting, as they aim to address several major challenges:

• Platform regulation: Can regulators approve a platform that generates multiple related therapies, rather than requiring each new payload to follow a largely separate development and approval pathway?
• Analytics and quality control: How can identity, potency, purity and safety be established rapidly for medicines that may never have existed before?
• Rapid release testing: If therapies need to move from design to patient in days rather than weeks, quality systems will need to evolve significantly.
• Software validation: If algorithms are selecting guide RNAs or editing constructs, software becomes GMP-critical. The manufacturing process could run perfectly, while the therapeutic design itself is incorrect.
• Safety assessment: Each new genetic sequence could introduce a different risk profile. The challenge is assessing that risk without recreating a full development programme for every therapy.
• Standardisation: A platform approach only works if most variables remain fixed, including the delivery vehicle, manufacturing process, analytics, automation and GMP controls. Ideally, only the payload and target binding change.

So, what is actually changing?

The most interesting thing about the convergence of the FDA guidance, THRIVE and GIVE is that they shift the conversation.

From a manufacturing technology perspective, platform-level regulatory acceptance and rapid quality control (QC)/release testing look like two of the most important enablers in making this happen.

Engineering the future of personalised genetic medicine

Programmes such as THRIVE and GIVE reinforce that the next phase of genetic medicine innovation will depend as much on regulation & engineering as on biology. Faster, more flexible and more personalised therapies will need automation, software, analytics, quality systems and regulated system development to work together.

As therapies become more personalised, analytics and rapid quality control will become increasingly important. Development teams will need analytical technologies, sensor systems and digital tools to support faster therapy characterisation and batch release.

Success will also depend on more than technical innovation alone. A clear understanding of evolving regulatory pathways will be essential to translate novel technologies into regulator-ready manufacturing systems that can be reliably deployed within GMP manufacturing environments. Throughout this process, human-centred design will remain essential to allow increasingly complex workflows to remain intuitive and usable for scientists, operators and clinicians.

If the industry moves towards common platforms that can support many therapies, the winners will need to integrate biology, engineering, software and quality systems into something robust, scalable and usable.