The age of blockbuster drugs has officially given way to precision medicines that are customized, using patient data, for rare diseases and individual patients. We are in the early days of a decades-long trend that will influence changes throughout the entire life sciences industry and lead to groundbreaking cures and treatments.
These new innovations are becoming the foundation of scientific discovery and with it, an explosion of available of scientific information and data – from clinical studies to real-world patient information – that is critical to finding patients to treat and keeping healthcare professionals and their organizations informed on the latest medicines. Getting the right information to the right people is critical for physicians in delivering the best possible care.
In 2020, we will see organizations better leverage this data across their organizations to accelerate the move toward patient-centered healthcare.
Here experts from Veeva, a cloud-computing company focused on pharmaceutical and life sciences industry applications, look ahead with their top predictions and the greatest areas of opportunity to improve patient health outcomes.
A connected and collaborative healthcare ecosystem will drive innovation
By Chris Moore—President, Veeva Europe
Healthcare spend is rising at an alarming rate, representing a striking 17% of total gross domestic product (GDP). Total U.S. medical spend as of early 2018 was $2.4 trillion1 with estimated preventable spending of $500 billion.2 As the population ages and the incidence of age-related and chronic diseases rises, the spending curve will eventually become unsustainable for societies around the world. Next year we’ll see a more dynamic healthcare environment take root with greater collaboration among biopharmaceutical companies, providers, and payers to drive greater efficiency throughout the industry and meet this growing challenge.
With the rising costs of healthcare, payers are only reimbursing premium prices for innovative treatments such as precision medicines that demonstrate higher efficacy among targeted patient populations. Precision medicines require the ability to identify patients with rare and individualized diseases. As a result, companies are becoming more agile and integrated within the healthcare ecosystems in which they operate to get the treatments to the patients that need them. This is driving new pricing models such as financial risk-based contracts, health outcomes contracts, and indication-specific pricing that are aligned with the unique characteristics of innovative products coming to market and, of course, the care needs of patients. 3
Moving forward to operate in this more interconnected and dynamic environment, companies will reduce siloed processes and systems both internally and across the healthcare ecosystem to drive new levels of operational efficiency and collaboration. This will not only enable life sciences companies to compete more effectively, but also work better with healthcare providers and payers in delivering the right care.
For example, we’ll begin to see a data flow from the patient or a healthcare professional directly through every part of the drug development and commercialization process, from regulatory and manufacturing to commercial and payment approval packages. This information will also flow to patients, payers, and providers as industry silos break down, giving the industry faster visibility into data so that treatment decisions can be made. Data will also be entered once but used many times, cutting half of today’s redundant processes and most duplicated systems. Companies ultimately will become more efficient and agile delivering their treatments to the right patients.
Once this new operating model for the industry is in place, artificial intelligence will be applied to monitor patterns, connect scientific discovery across teams, identify the best clinical trial sites, and match trial populations to treatment populations. This new will lead to safer, better outcomes and reduced waste throughout the industry.
- CMS, National Health Expenditures (figures as of 1/8/2018). Total medical spending equals health consumption expenditures minus retail sales of medical products,
- “Targeting High Cost Patients and their Needs, “Ashish K. Jha, MD, MPH, Harvard Global Health Institute, January 19, 2016
- “Six drug pricing models have emerged to improve product access and affordability.” https://www.pwc.com/us/en/industries/health-industries/library/6-drug-pricing-models.html
Privacy-safe analytics and AI will accelerate the shift to patient-centered healthcare
By Tom Schwenger—President and COO
In 2020, we will see two key trends collide – the continued shift toward personalized medicine and an increased focus on data privacy. Successful commercial teams will focus their execution of patient-centered healthcare for specialty conditions in a way that’s privacy-safe and more intelligent.
The advancements in specialty products, including personalized medicine, has led to more effective treatments and improved health outcomes for patients. For example, the use of specialty pharmacy care has provided a significantly lower risk of disease relapse for MS patients than traditional pharmacy care1.
However, the patient journey has become more complex, creating an opportunity for pharma manufacturers and hub services to better communicate and support patients and HCPs. Pharma sales and marketers will use privacy-safe predictive analytics to build a communications plan to engage HCPs at key moments along the patient journey. The use of AI will also give teams more detailed, person-level insights to more precisely identify and target patient populations and enhance their promotional strategies. HCPs and hub services can then, in turn, reach patients at the right time to drive better diagnosis, treatment, and adherence.
With an increased societal focus on privacy – and corresponding regulations like CCPA and GDPR – companies will need to balance helping patients navigate the complexity of the specialty market while also addressing patient privacy concerns, including allowing optional enrollment and the right level of opt-ins and opt-outs. In fact, a recent survey found that 78% of respondents said a company’s ability to keep their data private is extremely important.2
Data and analytics will continue to play a larger role in ensuring that life sciences companies reach the most relevant patients and HCPs in a privacy-safe way, and, ultimately, get more patients on the right treatments for improved health outcomes.
- Effects of Specialty Pharmacy Care on Health Outcomes in Multiple Sclerosis. Nov 16 – http://www.ahdbonline.com/issues/2016/november-2016-vol-9-no-8/2230-effects-of-specialty-pharmacy-care-on-health-outcomes-in-multiple-sclerosis
- IBM study: https://newsroom.ibm.com/Cybersecurity-and-Privacy-Research
AI becomes a real-time coach embedded in commercial processes
By Paul Shawah—Senior VP, Commercial Strategy
AI has proven extremely valuable in processing volumes of information and delivering insights and suggestions on the next best action to take, dramatically improving commercial effectiveness. Next year AI will become pervasive in enterprise applications and embedded within specific commercial workflows, expanding to become more context aware of what account teams are doing as they’re doing it and acting as a real-time coach.
AI delivers intelligence that is helping commercial organizations get the right information to HCPs to deliver the best possible care to patients. With the move toward patient-centric healthcare and more innovative precision medicines and specialty drugs, there is a wider variety of stakeholders involved in administering care. This is creating complexity in identifying the right patients, getting them on treatment, and managing all the services to drive adherence and patient outcomes.
As AI becomes more context aware of what account teams are working on, it will act as a real-time coach to help navigate this complicated ecosystem of stakeholders much easier. For example, AI can provide a recommendation on new HCPs to reach or account strategies to consider during account planning, helping teams drive better and more relevant engagement with the right targets at the right time.
AI will also enable real-time compliance. Commercial teams, for example, will be able to take detailed notes of customer interactions in CRM while AI provides real-time guidance about potential compliance risks such as off-label topics. With a real-time coach, commercial teams will have the freedom to share unstructured thinking and, ultimately, deeper insights without risk to drive more informed, compliant interactions.
Patients’ active role in their healthcare decisions will transform the industry’s model of care
By David Logue—Senior VP of Strategy, Veeva Europe
In the existing account-based model of healthcare, physicians have traditionally been the focus of manufacturer information, business development efforts, and support. The industry is still in the early stages of adopting a patient-driven model that examines patients holistically, as banking, entertainment, merchandising, and other industries have long since done. From the consumer perspective, healthcare is complex to navigate, fragmented, and exorbitant. In 2020, the industry will continue modernize and focus on the patient’s journey and experience in a way that results in more patient empowerment.
On the clinical side, pharma will focus on helping patients better research and understand medication options, risks, and outcomes. More collaboration within the industry to drive new products and ways of paying for them, particularly oncology and specialty treatments, will be an imperative.
On the commercial side, companies will better align their marketing efforts and account teams to focus targeted messaging to providers. For example, streamlining the process for medical legal review and use of digital publishing will help ensure timely communication of new discoveries, innovative treatments, clinical trials, and more to providers and patients.
While patients are provider network subscribers and research, treatment, and surgery candidates, they are also consumers in search of value, convenience, simplicity, and comfort. We see the industry adapting to address medical needs and deliver treatments to patients in ways that afford greater personal empowerment.
New trial designs will usher in a new era of clinical trial data management
By Richard Young— Senior VP, Clinical Data Strategy
As clinical trials evolve in the age of precision medicine and new trial designs emerge, pharma companies will be called upon to develop new approaches to collecting, using, reusing, and sharing trial data. Single use, throw-away data has been the mainstay within the clinical trial ecosystem, with as much as 80%1 of all data that’s collected being used only once.
In the coming year, we expect to see the growth of reusable patient and research data within the industry. EHR data will be combined with data from multiple trials to provide a repository of multi-sourced, multi-purposed data, analytics, and insights. Real-world evidence will be collected and examined throughout a patient’s lifetime to provide an historical perspective. This data will be applied not only to the individual patient, but to other patient populations to eliminate redundancy, streamline processes, and reduce trial costs.
Data management solutions that treat flexibility as a norm, rather than the exception, will be critical in enabling sponsors to change trial designs as new insights emerge. Large volumes of data will be captured both from conventional sources, as well as from new sources such as wearables and sensors, enabling more inputs to be operationalized in real-time. Companies will have greater latitude, not only in determining how trials are run, but also, in making trial design modifications on the fly. This transition from clinical data management to clinical data science will also give rise to a new view of the patient as a key contributor to the data science process rather than as a contributor of fluids and biomarkers.
1. Better Collaboration is Key to Speeding Trials,“ Contract Pharm, October 18,2019
Synthetic data unlocks the key to greater trial efficiency
By Henry Levy — General Manager, Veeva Vault CDMS
With today’s emphasis on outcome and value-based payment initiatives, the ability to analyze real-world patient data is important to discovering the best treatments and improving patient outcomes. EHR and clinical trial data sharing has emerged as a primary way to speed disease diagnosis and treatment. In the coming year, we anticipate the use of synthetic data to increase trial efficiency, reduce costs, and improve outcomes for all stakeholders, as well as safeguard against GDPR compliance risk.
Rather than collecting data from patients assigned to a control or standard-of-care arm, real-world data can be modeled for specific patient groups and potential outcomes. The use of this synthetic data holds vast promise in determining therapeutic regimens, identifying and mitigating drug side effects, and optimizing dosages and synergies in multi-drug therapies.
Synthetic data also has the potential to address compliance risk and privacy concerns. Real-world patient data is often siloed due to privacy concerns, but the use of synthetic data can be more accessible. While the full ramifications of GDPR within the healthcare industry has yet to be fully understood, one way to avoid potential compliance risk will be through the use of synthetic data.
New methods such as hybrid trials will improve patient enrollment and retention
By Jim Reilly – VP, Clinical Market Strategy
Low trial enrollment and retention presents a challenge throughout the industry, with up to 90% of studies in the US experiencing significant delays in recruitment and enrollment.1 Nearly one-third of all trials under-enroll, and only 7% meet their target enrollment number on deadline.2 Much of the challenge stems from geographic mismatch of site to patient, poor patient engagement, and lack of trial awareness among patients.
In the coming year, we anticipate that pharma companies will show measurable improvements in enrollment and retention through new methods that bring trials closer to patients. These include hybrid trial delivery, community-based sites, and digital engagement. Hybrid trials (as opposed to the all-or-nothing sounding term “virtual”) deliver parts of a trial digitally – from activity trackers and telehealth to e-consent, ePRO, and social apps.
Another novel idea being tested is the ability to professionalize remote or rural healthcare providers by outfitting them with training and equipment to deliver investigational treatments. Improvements in social engagement and data access will also drive better trial awareness and retention. All these methods will collectively improve trial enrollment throughout the industry.
- Dowling NM, Olson N, Mish T, Kaprakattu P, Gleason C. A model for the design and implementation of a participant recruitment registry for clinical studies of older adults. Clin.Trials 2012 Apr;9(2):204-14. PMCID:PMC3325341
2. Strasser JE, Cola PA, Rosenblum D. Evaluating various areas of process improvement in an effort to improve clinical research: discussions from the 2012 Clinical Translational Science Award (CTSA) Clinical Research Management workshop. Clin.Transl.Sci. 2013 Aug;6(4):317-20. PMCID:PMC3740438
Data curation becomes the lifeblood of organizational efficiency
By John Lawrie – VP, Veeva Vault RIM
Global health authorities are driving sponsors to maintain and submit increasingly large data sets. Next year pharma companies will evolve their business processes and operational mindset to comply. A vast majority of companies still rely on email, manual processes, and physical hand-offs to capture, document, and share information1 – a structure that is not sustainable as more regulatory controls are added throughout the supply chain.
For example, upcoming revisions to IDMP (Identification of Medicinal Products) and the FDA’s PQ/CMC (Pharmaceutical Quality/Chemistry Manufacturing and Control) initiative will intensify the need for data that is structured, harmonized to global standards, and easily accessible. New organizational roles that bridge the gap between the data needed for submissions and how that information is managed today will be created to ensure compliance goals can be met.
Data curation will become as important as document authoring and sit at the core of companies that nimbly adjust to evolving compliance standards and an ever-changing marketplace. Roles such as data curator and data scientist, along with the creation of specialty innovation teams that address stakeholder information needs and opportunities, will grow in stature. This shift will accelerate time to market, eliminate waste, and enhance patient safety.
1.Veeva 2019 Unified Clinical Operations Survey Report
Delivering better patient outcomes in 2020
The goal of precision medicine is to drive better patient outcomes through tailored treatment approaches. The intersection of this scientific discovery, new technology, and patients’ active role in their healthcare decisions will lead to even greater industry collaboration and connectedness. We’ll continue to see life sciences come together to put a holistic model of healthcare delivery in place to enable this new era of medicine for decades to come.