Metformin Sets Its Sights on Vision Loss
A common diabetes drug, metformin, is being repurposed and investigated for retinitis pigmentosa.
Retinitis pigmentosa (RP) refers to a group of inherited disorders affecting the retina.
The retina is a layer of photoreceptor cells at the back of the eye. Photoreceptors absorb light, triggering chemical changes that convert sensory input into signals that travel to the brain via the optic nerve.
RP-linked mutations affect photoreceptor function, resulting in vision loss over time. What starts as night blindness in childhood later progresses to peripheral vision loss, and for some, leads to legal blindness by midlife.
Over one million people live with RP; they rely on vision aids, assistive devices, and occupational therapy to adapt as the disease progresses. Researchers have identified numerous causative genes, but treatment is limited, with only one approved gene therapy for RPE65-mediated inherited RP.
Paul Michaels, chief executive officer at Curative Biotech, hopes to change this. In a conversation with Technology Networks, he shared his thoughts on mutation-agnostic therapies based on drug repurposing. As well as targeting multiple disease-causing mechanisms at once, this approach could also deliver therapies to patients sooner.
What evidence has highlighted metabolic dysfunction as a driver of retinal degeneration in RP?
Paul Michaels (PM):
Over the past decade, evidence has increasingly shown that RP is more than a collection of genetic disorders—it is also a disease of disrupted cellular metabolism. While inherited mutations initiate the disease, researchers have found that degeneration is accompanied by impaired mitochondrial function, oxidative stress, and reduced energy production within photoreceptors.
Rod photoreceptor loss also alters the metabolic environment needed to support cones, which are responsible for central and color vision. These downstream metabolic changes appear across multiple genetic forms of RP, suggesting they represent a common pathway driving disease progression.
That insight has shifted thinking beyond mutation-specific therapies toward approaches that preserve retinal health by restoring metabolic balance, potentially benefiting a much broader patient population.
IH:
PM:
Metformin is one of the most extensively studied medicines in clinical practice, with decades of safety data and well-characterized pharmacology.
Metformin for retinal degeneration
Metformin is the first-line medication used to treat type 2 diabetes. Curative Biotech has reformulated metformin into a topical, ophthalmic therapy for macular degeneration, and first-in-human trials are planned for 2026. Macular degeneration does not fall under RP, but there is some overlap in gene mutations and degenerative pathology. They are currently conducting preclinical studies on retinitis pigmentosa models.
Beyond diabetes, [metformin] influences fundamental pathways involved in cellular energy regulation, including activation of AMP-activated protein kinase, mitochondrial function, and oxidative stress.
Those mechanisms overlap with pathways increasingly implicated in retinal degeneration. Our interest is based on the hypothesis that improving metabolic resilience could help preserve photoreceptor survival regardless of the initiating mutation.
Repurposing a medicine with an established safety profile also provides the opportunity to evaluate this scientific hypothesis more efficiently than developing an entirely new drug, while maintaining the same rigorous standards for demonstrating efficacy in patients.
IH:
What are the key benefits and limitations of a mutation-agnostic approach compared with targeted therapies?
PM:
Targeted gene therapies represent an important advance and can provide transformative benefits for patients with specific mutations. However, RP involves more than 90 causative genes, making individualized therapies challenging for many patients.
“A mutation-agnostic approach focuses instead on biological processes shared across different forms of disease. If successful, it could reach a much larger population and simplify clinical development.” — Paul Michaels.
The challenge is demonstrating that a common metabolic mechanism is sufficiently important across genetically diverse patients. I view these strategies as complementary rather than competitive, with mutation-specific and mutation-agnostic therapies addressing different but equally important clinical needs.
IH:
What are the main factors that determine how quickly a repurposed therapy can enter clinical testing, especially considering the FDA’s 505(b)(2) pathway?
PM:
The availability of existing safety, manufacturing, and pharmacology data can significantly streamline development. The FDA’s 505(b)(2) pathway allows sponsors to leverage appropriate prior findings while generating new evidence for the proposed indication.
FDA 505(b)(2) pathway
The FDA’s 505(b)(2) pathway aims to streamline the drug approval process by allowing the use of existing data. This is particularly relevant to drug repurposing, where safety is established, or when new drugs are similar to those already approved. The goal is to move drugs into clinical testing at less cost and on shorter time scales.
“[The 505(b)(2) pathway] can reduce development time and risk, but it does not reduce the scientific bar.” — Paul Michaels.
Sponsors must still demonstrate that the therapy reaches the target tissue, establish appropriate dosing, and generate convincing clinical evidence of efficacy. Success ultimately depends on strong biology combined with well-designed clinical studies.
IH:
How could advances in systems biology help to identify new uses for established medicines across indications?
PM:
Systems biology enables researchers to examine disease as interconnected biological networks rather than isolated genes or proteins. By integrating genomics, transcriptomics, proteomics, metabolomics, and computational modeling, scientists can identify pathways shared across seemingly unrelated diseases. That makes it possible to recognize when an established medicine may influence a common mechanism beyond its original indication.
As artificial intelligence and computational biology continue to advance, I believe drug repurposing will become increasingly data-driven, enabling researchers to prioritize the most promising therapeutic opportunities while reducing development time, cost, and risk.
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