Precision Medicine, Trial Design, And Patient Centricity Will Remain Hot In 2016
By Ed Miseta, Chief Editor, Clinical Leader
Jennifer Reichuber, co-founder and principal at Altani Associates, has been a consultant to pharma and biotech companies for about four years. Prior to becoming a consultant, she was involved in clinical development at a Big Pharma company for 15 years. She has a unique breadth of experience as she started her career as a study coordinator for an infectious disease clinic in San Francisco, and also worked for a large technology company for a period of time. In her current role, Reichuber notes her passion lies in helping clients achieve their goal of getting needed medicines to patients faster and more efficiently. She is passionate about the intersection of health, technology and innovation – and how it all can support the concept of precision medicine.
Two of her current clients are Big Pharma companies, and four others are small biotech firms located in the San Diego area. One is a virtual biotech. She also works with a couple of small technology vendors operating in the mHealth space.
Her experience in healthcare, tech, and pharma, and as a consultant, has given her insights into the challenges these companies face, and their outlook on trends for 2016. When it comes to large pharma companies, she believes one of the challenges they will face is whether to pursue personalized medicine business models and products. Precision medicine, the medical model that suggests the customization of healthcare with medical decisions, practices, or product tailored to an individual patient, is a key focus for a subset of the biotech, pharma and technology industry. Things like big data analytics, patient-centricity, real world data/evidence, mHealth, telemedicine, etc. are all current trends in 2016 and beyond. Reichuber believes we are just scratching the surface of understanding these powerful and industry shifting topics.
“How companies set up or reorganize their data infrastructure, processes, and technologies to support the foundational decision of targeted precision products or the more general products will vary markedly depending on their choice,” she says. “When it comes to large pharma companies, trying to make changes in their operations and clinical systems is like trying to shift the Titanic. Their processes can be detailed and cumbersome, and their systems are complex both in terms of the number of systems in place and how they are connected. For a large pharma organization to be able to pivot to adapt and incorporate methods and models such as mHealth, clinical trial optimization, or real world data, it can be incredibly difficult. They are just unable to make changes as easily as smaller companies that are leaner, more agile, and do not have the same level of complexity, or perhaps even the foundational infrastructure. In this situation, being a less mature organization can really be an advantage.”
Know What Type Of Data You Will Manage
Reichuber has encountered companies that have chosen a strategy to pursue only personalized products or more general products. Others will choose to make that decision on a molecule by molecule or disease basis. Regardless of the approach, some of the real world data and real world evidence packages, as well as the wealth of unstructured data we have access to today, are simply not as applicable for those companies going after non-personalized products. Those companies will tend to pursue more of a traditional drug development model and forego incorporating the real world precision medicine data.
That said, Reichuber recognizes in either situation, companies need to get smart about incorporating input from payers and regulators much sooner in the process as we shift into the new health paradigm. Whether it is the incorporation of a new data type from wearables or telemedicine, a newly defined outcome, or a novel drug delivery process or device, companies need to understand and gain buy in early from both payers and regulators. Early engagement will smooth the way for expedited approvals.
What Reichuber finds exciting is the openness and engagement from the FDA and other regulatory agencies, as well as payers, to be a part of the dialogue and shift into the new paradigm. Training others, helping companies establish an operating model for, and facilitating design sessions is an innovative way that Jen and her team at Altani are supporting their clients.
For companies shifting focus towards personalized medicine, moving to that type of model from a traditional drug development model can be a challenge. The primary issue revolves around how to organize both structured and unstructured data. “Companies need to know how to set up data standards and how to set up structures and processes to make sure they are able to analyze the data,” notes Reichuber. “The challenge I have seen with the larger companies is they have created incredibly complex clinical and non-clinical system landscapes. They are now in a situation where they almost have to break it down and set up a new foundation that allows for a set of consistent data standards (when appropriate), yet is nimble enough to receive unstructured data. The companies that can set up the most standard, yet flexible data lakes, will have an advantage.”
Reichuber points to the large and powerful EDC and CTMS systems in place at many pharma companies as a big part of the problem. Ten years ago, they were the technologies of the future from a clinical and non-clinical data perspective. But today, the larger companies that have built infrastructures around these behemoth CTMS and clinical data systems now have to figure out a way for them to accommodate unstructured data, or identify ways in which the data can be utilized and useful for some level of analytics. According to Reichuber, they have a double challenge of re-structuring and then building it back up. Companies, regardless of size, can accomplish this by shifting the mindset to look beyond the constraints that exist today, and partner with those in the ecosystem around the business challenge, and co-create opportunities together.
Get Patients, Caregivers, Payers, And Clinicians To The Table
Another trend Reichuber still sees a lot of pharma companies focusing on is patient centricity. What she finds most interesting about it is the frustration she sees in companies as they try to define what it is, how they define it, what are they going to do about it. Whether the company is large or small, executives seem to want people to know they are serious about patient centricity.
“What many companies seem to be most focused on is creating patient advisory boards, or including the patient voice,” says Reichuber. “This is absolutely fantastic, but what I would love to see pharma focus on is incorporating the entire health ecosystem voice for that targeted therapeutic area. One way of doing this is by implementing a design thinking methodology. That is, how do you design clinical programs and trials that start with a focus on the needs of your end users – all of those in the health ecosystem? When you design your clinical plan, how do you consider the voice of the patients, payers, caregivers, clinicians and regulators? Additionally, in the global health space, or in vaccine development and other preventive medicines, you need to account for what we call health-centricity since your focus is prevention, before someone becomes a patient.”
Reichuber believes the design thinking methodology enables a process, and has really helped some of her clients in biotech and pharma. For most of them, the main question is how to bring the patient voice into the development plan process. Unfortunately, what she continues to see is companies performing a single advisory board, or including just the patient right before protocol finalization, and thinking they have all the information they need to design an effective trial. She would like to see them get that ecosystem of voices involved throughout the entire process, from the time of CDP and TPP development through study implementation, in an iterative design approach.
Many sponsors also worry about the legal and compliance ramifications of including non-company staff, such as a patient or caregiver, on development teams. “They cannot be an active patient, or caregiver of a patient, on your clinical trial, but they most certainly can be a patient with that disease or therapeutic,” she states. “Patients who have been through a similar trial in the past will generally be willing to tell you what they liked and disliked about it. That information can obviously be very valuable to the design team. I have worked on trials in both the oncology and non-oncology therapeutic areas. Patients who have been through a trial understand the value as well as the challenges of being a study participant. There are many simple things that can make a patient experience unpleasant which companies can easily overlook. By including the patient, caregiver, study coordinator and clinician in the design of your trial, you shift the focus to be co-creation and set yourself up for a much better success rate and higher patient engagement and attrition.”
Combine that with their agile processes and technology systems, you have more of an open playing field to drive precision medicine models and innovate in the space.
Finally, there are ways to incorporate the process and methodology of co-creation, design thinking, and iterative product development to make trial design more effective. There are ways to establish effective data lakes and information layers that will enable the intersection of use of unstructured and structured data. This will make drug approvals faster, and speed products and services to the patients, families and clinicians that need the help.