Delighted to have joined the OnHelix 2024 panel session on "New Horizons for Therapeutic Modalities". We explored a range of topics, and here are the main points I took away:
🤝 Multi-modality synergies 🤝
On the panel, we all agreed on the need for a diverse and comprehensive toolkit of different modalities, as there is no silver bullet. I would go one step further and say that different modalities can and should be combined to achieve greater impact. Think of mRNA (mRNA-4157 from Moderna) + antibody (Keytruda from Merck) for resected melanoma treatment. mRNA-4157 is a personalized neoantigen therapy that encodes up to 34 neoantigens derived from the patient's tumor mutational profile. When administered, these neoantigens are processed and presented by the body’s cells, triggering a tailored immune response specifically against the tumor. Keytruda works by enhancing the immune system's ability to detect and attack cancer cells by blocking the PD-1/PD-L1 pathway, which tumors use to evade immune detection. The synergistic action has shown promising results, with the combination therapy showing an 18-month recurrence-free survival 17% higher than monotherapy (see link in the comments below).
📈 More data doesn't mean better AI 📈
The cost of generating data in life sciences is dropping thanks to automation, making vast amounts of data available for both discovery and process automation. This treasure trove of data can be used to train AI/ML models to understand multifactorial diseases, develop advanced therapeutics, and optimize manufacturing processes to achieve better quality and economics. However, data accuracy, completeness, and standardization remain critical issues. The integration of data from disparate sources, each using different data standards and lacking semantic consistency, poses significant challenges. I came across a paper where the authors describe in detail how integrating different data sources with poor consistency actually decreases model accuracy to such an extent that it's not worth combining these sources if they are not aligned (see link in the comments below).
🕑 Move fast, break things...sort of 🕗
While cell and gene therapy manufacturing costs are rightly prioritized, the impact of development time on the overall economics of therapeutic development is equally significant. This issue was a focal point of the panel discussion, where panelists shared firsthand experiences and underscored the sluggishness of the design-build-test-learn cycle for CGT therapeutic development. Certainly, there isn't a single dominant cause of the slowdown; rather, several bottlenecks combine to delay progress and drive up costs.
But if you had to choose one, which major bottleneck do you face most frequently in the discovery phase of new CGT?
#ONHelix24 #CGT #mRNA
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6moFelicidades Mireia, cuando pases por Barcelona nos vemos :),