Failing Blockbuster Medicines, Eroding Operator Margins & Increased Pricing Pressures: What’s Next for Precision Medicine?
Posted 12th September 2018 by Kieran Chambers
The Precision Medicine and Biomarkers Leaders Summit: Europe takes place this week and in anticipation, we spoke to Unmesh Lal of Frost and Sullivan about his views on what the future holds for precision medicine and how the pharmaceutical industry has changed in recent times.
Can you tell us a little bit about your current position at Frost & Sullivan and what it entails?
I’m the program manager for the Life Sciences vertical in the transformational health practice at Frost & Sullivan. Apart from Life Sciences, we have three other verticals, which focus on imaging, advanced medical technology, and digital health. Our Life Sciences vertical is further broken down into the pharmaceutical & biotech and the next-generation diagnostics & research tools programs. From a strategy perspective, I track some of the innovative business models and the disruptive technologies when it comes to the core areas within pharmaceuticals and diagnostics. Within pharmaceuticals, we look at the key growth opportunities and game changing companies in drug discovery & development, targeted therapeutics, regenerative medicine and smart manufacturing.Within diagnostic and research tools, we track similar trends in point of care testing, molecular & companion diagnostics, lab automation and smart genomics.
In addition, we are focusing on future market trends impacting the shift from primary to speciality care, in-house to open innovation and outsourcing, bench to bedside diagnostics, research applications to clinical use and the overall impact of informatics and digital when it comes to post-diagnostics and preventative healthcare.
How has the precision medicine market changed in the last 5 years?
In general, over the past 5 to 10 years the pharmaceutical industry has witnessed declining research and development productivity, increased pricing pressures and deeply eroding operating margins. We are also seeing a failing blockbuster medicine model. Basically, it’s not a one-size-fits-all anymore. That’s why there is a need for precision medicine.
There’s been a change in the cost curve. People want health and not necessarily healthcare, which has led to the shift in focus and investments from acute care to prevention, which very much aligns to the phenomenon of precision medicine.
We have seen value-based care and population health management demand personalised and precision care delivery. Healthcare consumerism and the explosion that we’ve seen in regard to the patient data is enabling the individual level patient stratification, which is very critical for the precision health practice because at the end of the day, it’s all about the insights from the data.
We’re seeing the shift from treatment to overall prevention, diagnostics and monitoring, which is well aligned to the goal for precision medicine, which is enhancing the quality of life. It is moving towards patient engagement and disease management thereby promoting early diagnosis and reducing the overall cost of treatment. Now we are at the point where we are focusing on prevention and wellness, which is to manage and mitigate risks, which is basically keeping people healthy in the long run. The importance of data-driven precision medicine is going to increase multi-fold over the next 5 years.
A very interesting example of this is the acquisition of Flatiron Health by Roche. They are providing that data-driven insight, which is giving Roche a competitive advantage in the long run. This is just one instance of the therapeutic upgrade in the past five years when it comes to precision medicine.
What are your predictions for the next 5 years when it comes to Precision Medicine?
I prefer to refer to “precision medicine” as “precision health” because it’s not just medicine anymore. Traditionally, precision medicine is defined as an emerging approach for disease treatment and prevention that considers an individual, their environment and lifestyle. At Frost & Sullivan, we define precision medicine as an emerging concept to discover and develop evidence-based stratified medicine for intervention, behaviour, nutrition, and that enables disease prevention.
The end goal being the delivery of superior therapeutic outcomes for selected patients by integrating their individual health data and information. It’s a broader perspective when you’re talking about the precision health landscape, it’s not just limiting assets to medicine, it’s overall health and improving the quality of life for patients focusing on wellness and wellbeing in comparison to just being curative. It’s preventative.
By 2025, in companion diagnostic biomarker based targeted therapeutics, there will be a shift beyond oncology towards infectious, CNS and cardiovascular diseases. This will also happen in regards to molecular diagnostics and genomic technology as is seen with liquid biopsy and point of care testing technologies, which have started to compete against the established methods of diagnostics. These are all areas that will develop precision diagnostics in the near future.
We are also seeing a lot of interest in precision imaging, molecular imaging, and informatics solutions, which are critical for companies like GE, Siemens etc. We are witnessing high growth in areas like human specimen and imaging bio-banking services. These bio-banks are going to create a network or a hub-based model, providing online access to high-quality samples and images globally enabled by advanced data management and informatics solutions.
In addition, there will be significant uptake in molecular and clinical decision support systems (CDSS), the CDSS segment for example, will provide combined insight from omics, clinical, lifestyle and exogenous data points to facilitate personalised treatment decision making. The future lies in a connected ecosystem for precision health.
What would you say are the biggest challenges facing the Precision Medicine market at present?
- Interoperability. Costs roughly around 150,000 lives and $18.6 billion per year in regards to health data interoperability. Studies have shown around ~46% of US clinicians don’t have a complete view of their patients’ health records and history. In general, the concerns about interoperability are a major barrier. Recently, Microsoft, Amazon, Google, IBM, Oracle, and Salesforce issued a joint statement for healthcare interoperability.
- Cybersecurity. Healthcare data is around 10x the price of credit card data in the black market. Studies have shown that the US hospital cybersecurity market alone will cross $5 billion mark by 2021. Regulations will increasingly make technology solutions untenable unless security and privacy can be assured. To the extent that technology adoption is thwarted by security concerns, patient treatments are degraded, cost increased, and market potential reduced.
- User Mindset Some users feel the systems they have are clunky and not easy to use. Alert fatigue is a major barrier to acceptance. Some users, especially specialists feel their experience is proven and enough. Some physicians feel there are already too many IT-related requirements ranging from meaningful use to EHRs to ICD-10. CDSS becomes yet another digital bother. Additionally, there are various cost-related issues ranging from the cost of a resource to the costs of developing and maintaining a system.
- Value-based care and reimbursement 90% of top-selling blockbuster medicines only work for about 30% to 50% of the patients. Then you’re also seeing about 5% to 10% of healthcare costs are fraudulent.
- Data ownership and incentivising models for patients. Patients and consumers in general are taking a lot more ownership of their own data. Approximately 53% of patients in the US believe they own their healthcare data and 20% don’t even know. You’ve seen the market in regard to big data and analytics cross the $7.5 billion mark by 2020, so a huge focus on data, which also poses similar challenges.
- Healthcare consumerism. 70% of consumers in the US track their health symptoms, 74% appreciate receiving customised alert newsfeed post care; 41% of patients are changing their physician if they are not allowed to access their health records.
How will the role of AI grow in precision medicine?
Through analysis of the vast healthcare data (medical literature, genomic profiles, EHRs), AI platforms will support in generating hypothesis, providing recommendations and preparing patient-specific treatment plans, resulting in efficient outcomes, reduced errors and lower costs.
There will be more AI educated professionals (doctors, primary care specialists) and departments (hospitals, ACOs) applying CDSS in daily life. By 2025, the next generation of medical AI systems would have “learned” from their past experiences based on patient, doctor responses and treatment outcomes.
Democratisation of AI would lead to cheaper AI-as-a-service models and services, ultimately leading to more than 90% of care providers worldwide (in developed and developing nations) adopting cognitive AI help as evidence-driven care for their patients. Artificial Intelligence will be used to handle and overcome epidemics by predicting forecasts from past experiences, in the creation of designer treatments, as well as in finding cures to deadly diseases.
Unmesh Lal will give his presentation “Real World Evidence- From Activity to Impact in Precision Health Decision Making” at the Precision Medicine and Biomarkers Leaders Summit.
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