Science is a game won with time and patience, through trials where errors far outweigh success. In the race against deadly diseases – COVID-19 among them – time is, of course, of the essence. And high-tech – specifically, high-tech platforms employing machine learning (ML) and artificial intelligence (AI) – can help speed up medical breakthroughs.
Pfizer and Moderna have each reported that vaccines have been developed that act as effective treatments against the coronavirus. Beyond the initial excitement (and hope) that comes with the companies’ claims of the vaccines’ high effectiveness in the latest rounds of trials (at roughly 95 percent) come the additional ripple effects from how these vaccines were developed and what the tech-driven implications might be for future drug development.
As noted by The Wall Street Journal, the Moderna and Pfizer developments show that gene-based technologies can pave the way for a range of new therapies that take aim at scourges like cancer and heart disease. In terms of the science, the gene-based developments – in this case, messenger RNA (or mRNA) – coax cells to produce proteins that are similar to the ones found in the coronavirus, and then set up the body to produce an immune response.
And it is in the development in mRNA that we see the embrace of platforms (specifically vaccine platforms tied to gene sequencing) and the innovation that comes with those platforms, marked by scale and speed.
In Nature Reviews Drug Discovery, for example, comes the observation: “Various mRNA vaccine platforms have been developed in recent years and validated in studies of immunogenicity and efficacy. Engineering of the RNA sequence has rendered synthetic mRNA more translatable than ever before.” This implies that the “classic” system of drug development, focusing on a pathogen-specific approach to develop immunity, can be augmented (or sidestepped, perhaps) with platforms. The result is that promising drug candidates can be developed in weeks, not years.
In a paper published by the Johns Hopkins Center for Health Security, the authors contend that platforms can use the same data to target more than one vaccine: Data is key.
As reported in Drug Development & Delivery: “Platform technologies are considered a valuable tool to improve efficiency and quality in drug product development. The basic idea is that a platform, in combination with a risk-based approach, is the most systematic method to leverage prior knowledge for a given new molecule. Furthermore, such a platform enables a continuous improvement by adding data for every new molecule developed by this approach, increasing the robustness of the platform.”
Moderna, for its part, has said that “if using mRNA as a medicine works for one disease, it should work for many diseases. And, if this is possible – given the right approach and infrastructure – it could meaningfully improve how medicines are discovered, developed and manufactured.” Against that backdrop, the company created its mRNA technology platform, which the company said functions in ways akin to computer operating systems – with plug-and-play functionality (and mRNA, the company said, is “the software of life”).
Other firms, of course, have also been building innovation platforms. Over the summer, IBM debuted its IBM RXN for Chemistry, billed as a free AI web service for predicting chemical reactions. There are also open-source pharma approaches.
The Platform Wins – from Big Tech to Big Pharma
The tech-driven platform approach echoes platforms seen in other areas of innovation – notably, those of companies like Uber, and even open banking. Connections are key – the kinds made possible only by advanced technologies.
Here, companies use data to scale, to build horizontal and ancillary products and services that leverage the same information to serve new use cases. In one example, Uber said it would branch out into software — specifically, software as a service (SaaS).
The same platform enables the creation, and service of, business lines as diverse as ride-hailing, food delivery and freight. Open banking allows for account data to seed and give rise to new services with shortened (tech) development times. As Karen Webster wrote in this space of Uber: “For Uber, transportation is a platform feature that is central to its business, but is not its end game.”
Similarly, for drug development, the genetic data can be used and accessed – and reused – by a range of innovators. It’s a shorter leap than we’d might otherwise see, from the data and the software … to the needle and a public health crisis conquered.
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