Reuters Events | Pharma

Thought leadership and innovation for the Pharmaceutical Industry

You can bet your bottom dollar that as your eyes scroll over these words there is a room full of pharma executives somewhere thrashing out a strategy towards precision medicine. A topic that was once confined to blue-sky conversations is fast becoming a reality.

 

Greenshoots are emerging in certain areas of the industry, says Jamie Heywood, co-founder and chairman of personalised health network PatientsLikeMe. “Individualised care is emerging in oncology where we have moved from tissue specific treatment to a new modality of genomic pathways that redefines how we looked at and care for cancer patients. The immune system is an area where individualised care is also emerging again, first in oncology with the prediction of response to immune activators. 

 

“Looking forward, I am excited about the research we and others are doing in inflammatory mediated disease. There are clear indications of sub typing of disease and treatment response that should lead to a similar shift to pathway specific care for rheumatology, neurology, and mental health. What makes this second area exciting is the crossover between disease, health and aging where individualisation has the potential to affect a much larger number of people.”

 

As a result, preparation is now mission critical, warns Heywood. Those developing drugs today must be prepared for the sea change or risk expensive product failure. 

 

“Pharma needs to be prepared for markets to be unstable. If you are developing a drug for IBS or IBD now, for example, and you expect that market not to split based on new diagnostics, you are going to be in trouble.”

 

Implicit in his warning is a clarion call. Pharma and the healthcare industry have not been thinking with sufficient scope or ambition when it comes to the possibilities. It is an iconoclastic approach but in Heywood’s view personalisation requires a new conceptual framework that is at odds with the one that dominates in pharma and healthcare today. 

 

The chief barriers are cultural among established pharma players, including what he describes as pharma’s ‘obsession’ with hypothesis-driven research which can prioritise expertise over high-quality de novo data. 

 

“What’s missing is a shift in thinking about what it means to understand patients holistically from using emerging technology and to involve them ethically and thoughtfully. The focus on the false idea of ‘validation’ versus actionability and meaning is driven partly by concerns of being criticised for using ‘invalid’ evidence in decision-making.”

 

Lastly, we build siloed data and hamper outcomes-based approaches, he adds. “Each clinical trial today is a siloed set of facts. We rarely integrate information into a holistic knowledge core for new learning.”

“The combination of hypothesis, validation and siloed thinking means that we do not build a common unbiased knowledge core, and we hesitate to apply emerging knowledge and we can’t assemble the raw data across studies. In short, we are biased, slow and siloed.”

 

It’s not all doom and gloom 

There are already signs that early adopters of precision medicine approaches are already bearing fruits, according to research conducted by The Economist Intelligence Unit and commissioned by Parexel. 

 

The research found the precision-medicine trial designs improved the likelihood of launch across all therapy areas by 10%, and had a significant impact on the ability to bring a drug to market in oncology, where the difference between precision and non-precision trial designs was 26%. “This shows the potential of these approaches to impact our ability to effectively bring much needed medicines to patients, particularly in oncology,” says Anita Nelsen, Vice-President of Translational Medicine at Parexel.

 

Personalisation promises to transform clinical trials too. The increased ability to precisely measure an individual’s biology and to view the relationship between that biology and the disease at both the level of the individual and the wider population promises to be transformative.

 

Heywood cites the adaptive trials work of Laura Esserman, Professor of Surgery and Radiology at the University of California, San Francisco as a good example. He believes similar innovation will occur in inflammatory and other medical conditions. “We can do the same with the immune system. Diseases like osteo and rheumatoid arthritis or lupus are going to be redefined,” says Heywood.

 

“I don't see clinical trials going away soon but what I think we will see emerge is something very different,” says Heywood. “It is going to be built on a new architecture that will provide comparable biology and it will be directly connected to clinical care”. 

 

The changing architecture of clinical trials will not be without its challenges, says Malia Lewin, Director for Global Oncology Strategy at Veeva Systems. 

 

Pharma will need to work with the healthcare sector on a far wider cross disciplinary basis to help define trials and feasibility studies in a world of individualised medicine. This will include collaborating in greater depth with pathologists, as well as the physicians who are working with the specific patient populations.

 

Specialists in health economics and outcomes research, econometricians, and RWE experts will also have a role to play in helping define what success will look like for particular products and in helping to perfect treatments as real-world treatment data is fed back post-trial. 

 

Touching distance

Transformative machine learning insights are near-term, not some future pipe dream, Heywood believes. “High quality analysis of individuals is going to provide massive insight and nuance into targeting, dosing, tolerability and management of adverse events.” 

 

The industry is under-estimating how powerful machine learning and the power of data informatics will be in delivering these insights, says Heywood. “Looking at the data in my system, I can see it will change targeting, success rates and risk in the next few years.”

 

The platforms and networks that gather and sift the data that will be the fuel for these insights are being built by the likes of PatientsLikeMe and health-related big data platform iCarbonX (which took a $100 million minority stake in PatientsLikeMe in early 2017). 

 

These companies are key players in the learning ‘ecosystem’, called the Digital Life Alliance: a network of companies involved in healthy living, disease and AI designed to accelerate the pace of innovation, improve the capabilities to interpret and mine ‘multi’-omics (proteome, metabiome, microbiome and so on) data along with phenotypic, behavioural, social, and environmental data.

 

One signpost towards a future in which greater sharing of data leads to better outcomes driven by personalisation is Sweden’s success in publishing the outputs of a number of disease specific registries that has led to dramatic improvements. In the US competitive dynamics among transplant centres provide another potential model for how new learning can be shared and applied rapidly in a world where data can be used where it has most value. 

 

“In the transplant community if you do not maintain incredibly high [survival] numbers you are effectively shut down,” says Heywood. “There is a huge economic incentive to perform highly against the metrics required by the transplant registry. Sadly though, despite this success, in the vast majority of medicine there is essentially no feedback on effectiveness.” 

 

Progress towards a broad adoption of individualised medicine will be also be through wealthy individuals keen to tailor their own treatments especially in the case of aging based advanced diagnostics, he says. “I believe the market will move through consumer direct pay in small micro markets and then eventually the broader market and reimbursement will follow.”

 

Ultimately individualised medicine will evolve into a world of ‘health banking’ in which we each have our own optimal model of wellness that enables us to achieve and maintain good health. “We are each healthy in a unique way,” says Heywood. “How do you store and understand the healthy version of you so that when you become ill for environmental, behavioural, genetic or infectious reasons, there is a baseline that shows the path back the healthy version of you?” 

 

The resulting opportunities would be vast. “If you can measure health broadly you can begin to look at health management as asset management. There is a huge market there if you can quantify the health of each person as an insurer and then begin to reward people for enabling measurable transitions towards individual health.” 

 

The broader social and economic prizes are vast too, he adds. “Much of what we spend in healthcare is misdirected or wasted. If we could begin to look at health as an asset that we manage, we could potentially free up five percent of the global economy to do other, worthwhile things.”

 

Commercial conundrum 

Personalisation poses challenges to every pharma player when it comes to commercialising new products, owing to the rapid profusion of different products and the resulting choices healthcare providers will have. 

 

The hundreds of novel cancer drugs available and in the pipeline is an indicator of how complex things could get. “The amount of noise in the space is tremendous. Patients have many treatment options available and more are on the way. More people want to talk to experts about what new discoveries mean for them and their cancer. Physicians are overwhelmed with patient requests and this is making it tough for industry to secure the time and attention for intelligent conversations with experts,” says Lewin.

 

Pharma field teams will need to help healthcare professionals sift a growing body of data, says Lewin. “It is changing the entire way the pharma industry is interacting with their key customers.

You can’t just talk to them about the product. You have to work out how it fits into an overall landscape in order to get the treatment to the right patient at the right time in their cancer journey. That requires education and the maintenance of knowledge.”

 

Understanding physicians needs and meeting them is likely to become even more important, says Lewin. “One challenge for pharma is how to make the most of every interaction with healthcare professionals.”

 

This will include helping to educate physicians on when to use different treatments and providing information tailored to where physicians are in their career journey, what experience they have with particular tumour types, and their familiarity with various treatments and their associated data. Further, understanding the ways they interact with others on the treatment team, such as pathologists, nurses, and nurse navigators, and helping them share information with the team in the way that those providers need to be engaged will also be important, adds Lewin.

 

This will also have an impact on the manner in which pharma interacts and communicates with healthcare professionals, such as offering more tailored digital content delivery, adds Lewin. 

 

“We are at the point where we can imagine that each of us gets guidance based on the experience of everyone ‘like us’ that has come before and our choice and experience would guide the next person,” adds Heywood – now that would be individualised medicine.