Initial in vivo validation of novel cancer therapeutics using AI

What were the specific results and observations from the 28-day mouse trial conducted by Oxford Drug Design?

The trial was a standard mouse xenograft against MCF7 breast cancer cells inserted into the fat pad. There were six mice per arm with the vehicle control and the positive control being the potent immunosuppressor agent rapamycin. We tested the current lead compound in our program and the results demonstrated clear efficacy with significant tumour regression. We also showed a well-defined dose response across the full range of our drug at 0-30 mg/kg.

How might this successful in vivo validation for the development of first-in-class cancer treatments advance current therapeutic options for multiple tumours?

This encouraging result was remarkably obtained already in our very first mouse xenograft and with our very first compound. So, it is all unoptimised. The potential to improve all aspects of our drug candidate from this point onwards is therefore very promising considering such an advanced start. We are already conducting further xenografts against colorectal cancer in collaboration with the UK’s foremost oncology institute, Cancer Research UK Scotland Institute (CRUK SI). Further in vivo studies are already planned against other tumour types as well. All along we will be optimising our compounds for improved efficacy and other parameters. So, the therapeutic potential for our program stands to increase from its current stage.

How does Oxford Drug Design’s AI drug discovery platform, SynthAI, contribute to the creation of cancer treatments that are more precise and less toxic compared to traditional methods?

Our proprietary, pioneering SynthAI capability is unique in the market in that it delivers highly efficient results fulfilling two key criteria simultaneously for best-in-class computational drug discovery. Firstly, SynthAI exclusively produces drug candidates which can be made feasibly by chemical means and furthermore that can be manufactured in an economically viable way once the candidate is prospectively approved for commercialisation. Secondly, it produces compounds which have the potential biological activity desired. This streamlined precision stands therefore to deliver more efficacious and safer therapeutics in less time.

In what ways does the precision provided by SynthAI impact the overall efficiency and cost-effectiveness of developing new cancer treatments?

The distinctive strengths and precision of SynthAI results as described thus stand to accelerate and make more economical the discovery and development of novel cancer therapeutics. The platform is furthermore disease-agnostic so it can be equally applied to efficiently discover more precise and safer medicines against other serious conditions with unmet need. We welcome interest from pharma and biotech companies like others which have already started to work with us collaboratively and we can apply our SynthAI tools to resolve their own drug discovery challenges cost-effectively.

How does Oxford Drug Design plan to advance their AI-driven cancer treatments towards clinical trials and potential market approval?

We are currently advancing in the preclinical stages of development, specifically in the optimisation phase. The ongoing work, for which we are seeking investment funding, should lead us to select the optimal candidate molecule which will then be taken into the human clinical trials. With the help of SynthAI alongside our biochemical expertise, Oxford Drug Design therapies therefore stand to eventually deliver superior therapeutic options to oncologists for a variety of treatments.

This is Oxford Drug Design’s second first-in-class therapeutic program achieving clear in vivo validation based on its AI drug discovery platform. The company is now focused on bringing this potentially superior first-in-class treatment into the clinic while equally efficient expansions of this differentiated capability are already planned to other disease areas with unmet need. Overall, its integrated expertise in generative AI and tRNA-synthetase drug discovery has the potential to have a powerful impact on the treatment of cancers where existing treatments have serious drawbacks.