Earlier this month, artificial intelligence (AI) and machine learning (ML) focused protein and biotech company Lila Biologics announced a global licensing collaboration with pharmaceutical giant Eli Lilly. The agreement will focus on the research and development of radioligands for the imaging and treatment of solid tumors, exploring multiple targets utilizing Lila’s AI and ML protein platforms.
Radioligand therapy is a form of oncology treatment, whereby a cancer-specific molecule is bound to a radioactive isotope, allowing selective destruction of cancerous cells while leaving healthy cells theoretically unharmed. But Lila offers a competitive edge; its AI and ML platforms can discover entirely unknown receptor targets, and engineer binding molecules with high specificity. It’s no wonder that Lila originates from Nobel-laureate David Baker’s lab.
“We’ve developed computationally designed mini-proteins that have really amazing properties,” commented CEO and co-founder of Lila Jake Kraft in an interview with BioXconomy. “We have unparalleled design capabilities to control where our molecules go in the body, to tightly bind to the tumor and clear rapidly from healthy tissue.”
The agreement with Lilly will allow Lila to retain full asset rights to its proprietary technology and pipelines. This is separate from the solid tumor-targeting radioligands it will partner with Lilly on. The research collaboration will mainly comprise investigational new drug (IND)-enabling studies, global clinical development and potential commercialization of AI-driven radiotherapies.
“Before ML, the success rate for binder design was less than 1%, depending on the receptor. Now we can get nanomolar binding from the first round, so from our perspective binder design is a solved problem,” Anindya Roy, co-founder of Lila, said. “We can design a molecule that is super stable, with really high affinity that can be heated to up to 200 degrees and remain exactly the same.”
In recent years, the potential improved safety profiles of radioligands for cancer patients has excited the scientific community, showing improved retention of radiation in cancerous cells while leaving healthy cells untouched. But Lila’s claims its AI platforms can take this one step further by predicting the clearance rates of its engineered molecules.
“We are able to exquisitely model how long the molecule stays in the body and that actually translates to the safety profile,” noted Roy.
And the choice for Lila to partner with Lilly was a shrewd one for both parties. “It actually took one call to get Lilly excited,” Roy told BioXconomy. “What motivated us to select Lilly is their expertise in the disease space and their amazing reputation. They can rapidly and efficiently develop medicines, and this gives Lila an opportunity to develop multiple targeted radiotherapies.”
And the future for radioligand therapies – as well as other cancer-targeting drugs with high specificity – seems bright. “Chemotherapy is so hard to administer, it’s so cumbersome to the patient and has so many side effects […] targeted therapy is the next generation of cancer therapy,” explained Roy.
But could these targeted oncology treatments make cytotoxic chemotherapy agents a thing of the past?
“The goal is a curative therapy. There is hope in 10–15 years to replace chemotherapy with solid tumors. With Lilly, around 2028 we could be in clinical trials,” said Roy and Kraft.
Quotes have been lightly edited for clarity.
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