38-39 - The missing piece of the puzzle

Life sciences research and development has been modelling disease, wellness and the impact of therapeutics with little consideration of the human microbiome. Although biologists have known something of its role, reliable data science has not existed to support robust evidence of correlations between a pharmaceutical product and the microbiology of the recipient (which in turn has a bearing on the immune response, allergic responses and more).

Arguably, the human microbiome and the wider planetary microbial ecosystem have taken a hard hit over the last 50 plus years. Intensive farming, overuse of chemicals in the soil and antibiotics in the food chain, alongside a preference for convenience and processed foods have left even the richest nations undernourished, which is having a detrimental effect on public health. The impact can be seen in the rise in diabetes, asthma and other long-term health issues across large populations. Reversing these negative consequences requires an appreciation of what has gone wrong, as well as an understanding of how to put matters right. This demands an understanding of the workings of the microbiome.

Bill Gates, the co-founder of Microsoft and now a philanthropist and advocate for global health transformation, believes passionately in the transformative potential of interventions involving the microbiome. He is not the only one. Stimulated by COVID-19, stakeholders from across multiple sectors have recommitted their focus to wellness and the notions of ‘food as medicine’ and ‘bugs as drugs’ (prebiotics and probiotics are examples here).

While influencing human genetics – another field of biology attracting significant attention – can take generations to have an impact, the opportunity to continuously improve the human microbiome and produce positive health outcomes is thought to be substantial. Particularly now with COVID, there is an intense focus on microorganisms and how people can stay healthy and combat the virus. There is a growing mindset that COVID’s damage to cells enables other bacteria to get a better foothold.

Unsurprisingly, there is a substantial business opportunity attached to the field. McKinsey’s report The Bio Revolution (May 2020) suggests that many trillions of dollars of business opportunity could be unlocked with a greater understanding of the microbiome, and that’s in life sciences alone. Beyond ambitious biotech companies, agricultural innovators, food manufacturers, governments and safety regulators are all keen to harness the potential.

Yet, before they can do any of this, even the most ambitious organisations need to be able to analyse and understand the microbiome – something which has been almost impossible until now.

Microbiome science has lagged behind other fields because there has been no real way to combine all of the complex and disparate data sets and cross-compare them to produce reliable conclusions about the interplay of different medicinal ingredients or nutritional elements on a person’s microbiology.

This advanced, multidimensional data science capability is critical to support advances in immunopharmacology – ie working with the microbiome, or improving its health, to produce better patient outcomes. Trailblazers such as Finch Therapeutics, Microbiotica and Seres Therapeutics are among the innovative therapeutics companies working to develop products in this area, for example using microorganisms as the primary mode of addressing gut disorders. More generally, there are lots of other pharma companies that want to understand the role of a good or bad microbiome in metabolising drugs and determining their efficacy.

To support their endeavours, and to provide scientific evidence in support of their products, these R&D innovators need the ability to apply microbiome science to their investigations and developments. The ability to do this will facilitate the development of more stratified therapeutics, that target treatments more specifically at a certain category of patient. This is also the way research in other fields, such as cosmetics, personalised care and nutrition, is heading.

Technologically, scientists are at a critical point now with microbiome discovery. Previously, the technology wasn’t there to allow reliable signals to be detected and move knowledge forward, but this situation is changing rapidly.

There is growing agreement that network science (by which we mean understanding broader biological interactions fully, in the current context) will be the foundation for life sciences in the future. This involves being able to explore data in a more connected way – which is becoming possible now, using the latest multidimensional data analytics and knowledge discovery, all powered in the cloud and advancing AI technologies.

We are now getting to a point at which it is possible for companies to access big data and apply sophisticated analytics to complex data sets and constellations of data, to derive correlations and explore causal relationships with the help of artificial intelligence to distil meaningful insights from them.

There are still some practical hurdles to overcome, particularly around data standardisation. Yet, advances in so-called graph databases (which map relationships between diverse data sets), AI-based analytics and the mainstream accessibility of powerful computer processing are allowing life sciences R&D organisations to distil new, credible scientific evidence about their products’ interactions with the microbiome to help advance product innovation.

Within the next decade, as more is done to standardise the metadata that describes scientific data, so it can be combined and cross-analysed reliably, we can expect to achieve a much deeper understanding of the microbiome.

Once life sciences innovators are able to combine their own findings with external data (from sources such as the European Bioinformatics Institute), this could help accelerate their endeavours, by promoting a deeper understanding of the role of the microbiome in the performance of their products. More distributed analysis and connective learning will enable companies to make bigger strides forward. The good news is that there is now a greater willingness among different organisations to pool their data so it can drive step-changes in scientific discovery, which will help accelerate progress.

The urgency around COVID-19 has inspired global collaboration at an unprecedented level, which bodes well for further life sciences breakthroughs once there is greater agreement around how data is formatted and described, making it easier to cross-analyse.

As the digital ecosystem for microbiome research develops, greater data standardisation and collaboration will underpin a growing ability to derive the data needed for scientific discovery quickly and effectively.