Open science, genomics, and the quiet revolution in our approach to pharma


Evan Floden, CEO of Seqera Labs examines how data sharing platforms are impacting cancer and genomics research.

The tide has been turning in the worlds of diagnostics and drug development. Bioinformatics and genetic sequencing are starting to be placed front and centre of public research programmes as scientists from around the world recognise the substantial benefits of knowledge sharing and resource pooling when it comes to genetic science. Increasingly, major collaborative life sciences projects, like the Human Genome Project or Human Cell Atlas, are driving advancements and organisations – both public and private – are taking note.

A recent flurry of announcements indicates increasing interest and trust from major public health organisations in the power of genomics. Boosting genomics-driven insights has been put front and centre of the UK’s Health Security Agency’s 10-year science strategy. The agency cited the incredible benefits seen during the Covid-19 pandemic when it comes to the UK’s ability to monitor and report on new Covid variants. In the US, the Biden administration has made advancing precision medicine, multi-omics, cell therapies and artificial intelligence-driven drug development all a priority in its 20-year plan. Each of these areas was identified as crucial for the US’s ability to monitor potential health threats and manufacture increasingly precise and innovative medicines.

This increased interest and potential for significant public investment in bioinformatics-led insights should not strike anyone as surprising. Bioinformatics and sequencing technology have provided the grounding for some of the most forward-looking scientific research for many years now, with precise sequencing tools and genomic research leading to increasingly sophisticated treatment avenues. Huge advancements in areas such as oncology include the advent of BioNTech’s mRNA cancer vaccine trials in the UK as soon as 2023.

What is perhaps more surprising is what has facilitated these advancements. Improved technology has secured the infrastructure needed to analyse genomic, proteomic, and metabolomic datasets at scale which has been crucial for development. But it is the fact that pharmaceutical and biotech companies are now sharing their cutting-edge bioinformatics data on open-source platforms for others to use for genomic sequencing that is truly speeding up innovation and saving even more lives.

What does open science look like?

When we talk about open science this is precisely what we mean. It is the sort of collaboration that started to happen on websites like GitHub and is now facilitated by integrated workflow tools that allow for data analysis pipelines to be shared and run across different platforms, organisations and even continents. These tools allow scientists to not just build on the work of others, avoiding repetition and increasing efficiency, but also to learn from researchers in other organisations and from other countries.

This has given rise to greater interdisciplinary collaboration, which has also become a feature of the current research process – developments in computer science and statistics are now embedded in the processes used by those working in biological and medical sciences. This is also allowing for transformation at much higher speeds with the development of new sequencing technologies being mirrored by tailor-made programme refits within orchestration tools.

The key question, however, is how this translates into better outcomes for scientists; how this empowers researchers with the tools to drive new discoveries and new innovations.

Reshaping drug discovery

Improved workflow management software can help scientists to develop predictive models for disease diagnosis, prognosis, and treatment in real-time. Pipeline tools can be collaboratively developed which standardise the way patient data sets are analysed and reveal patterns that are indicative of disease progression or treatment response. Such tools used to be developed and redeveloped – at high cost – by organisations looking to innovate in the same areas and were often hampered by potential inaccuracies, with errors being missed and the end results compromised.

Now, improved pipeline infrastructure is providing the foundation for discovering revolutionary ways for diseases to be diagnosed and treated, leading to more effective and targeted therapies. The bottom line of a collaborative approach that utilises scalable data orchestration tools is the faster discovery of new therapies.

A prominent example is the use of data orchestration tools to analyse the genetic basis of diseases and identify genetic variations associated with disease susceptibility, progression, and response to treatment. This has led to the development of personalised medicine, where treatment decisions are based on an individual’s unique genetic profile instead of, for example, prescribing the same dose of medicine for a child and an adult male with diabetes.

How open-source data is benefiting the population’s health

It is worth emphasising how much of a step-change this collaborative shift in global science could be. Pharmaceuticals and drug discovery have had something of an IP-intensive reputation for many years now, with knowledge sharing appearing to be a far-off ideal. However, open-source pipeline infrastructure has provided the basis for a new way to share insights, and for researchers across the world to come together to drive innovation.

As we see interest and investment in personalised medicines to treat diseases of all kinds, such infrastructure will prove essential in building scalable and repeatable tools which point to potential cures based on an individual’s genomic data. Saving both money and time by drawing on open access data from scientists working in similar areas will allow for money to be reinvested and has, for the first time, freed up funds to allocate to the study of rarer diseases.

But it is not only the threat of rare diseases that is being addressed. As potential health emergencies such as avian flu and diseases borne by ticks and mosquitoes loom, national institutions such as the UKHSA are right to be embedding sturdy infrastructure within the healthcare system to combat them. Looking to the future, there is undoubtedly scope for genomics to become the foundation for even more national and international collaboration to improve public health. But without the use of technology that facilitates the open approach to science solidifying this foundation, innovation will move at a far slower pace.

DDW Volume 24 – Issue 3, Summer 2023

Evan FlodenAbout the author:

Evan Floden is co-founder and CEO of secure workflow orchestration platform, Seqera Labs, which has a global community of over 15,000 researchers and works with thousands of organisations including top US universities and pharma companies such as AstraZeneca.

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