The Randomized Controlled Trial is the Gold Standard for Clinical EvidenceIs it a Barrier to Innovation?

Tim Fayram MSVice President of ResearchSunnyvale, CANovember 19, 2013

IntroductionWho is Vinod Klosla?

E t i l i i th SiliEntrepreneurial icon in the Silicon ValleyCo-founder of Sun Microsystems andCo founder of Sun Microsystems and Daisy SystemsNow leads Khosla VenturesViews on healthcare at a talk on the Stanford University Campus in June of 20122012

IntroductionHealthcare Innovation in the next 5 years …

Approximately 500M people haveApproximately 500M people have access to healthcareApproximately 6B people don’t have access to healthcare and want accessWe face a rapidly increasing slope onWe face a rapidly increasing slope on the cost versus time graphHow will the healthcare delivery ymodel adapt in the next 5 years?

IntroductionTechnology is our only hope …"Almost everything doctors know about medicine will be obsolete "medicine will be obsolete,

Most Physicians and Clinicians as we know them will be replaced by

Computers and robotics for diagnosis and treatmentMobile devices will guide patients in the management of their disease statesBig Data analysis of huge patient groups will lead to the development of new treatment strategiesI ti th t h t t hInnovation that has yet to happen

All of this will come at a much lower treatment cost per patient

The Healthcare Landscape: Is the focus on Outcomes and Comparative Effectiveness?Outcomes and Comparative Effectiveness?

Medical Device Epidemiology NetworkMedical Device Epidemiology Network Initiative (MDEpiNet)

5

Healthcare Public PolicyA dynamic environment

Implementation of the Affordable Care ActA conservative regulatory approach seemsA conservative regulatory approach seems to be subsidingA reimbursement approach that is asking for additional proof and is paying out lessadditional proof and is paying out lessThe rise of the Accountable Care OrganizationComparative effectiveness researchComparative effectiveness research

There are conflicting signals but the need for cost effectiveness evidence is stronger than ever before

EvidenceNew types of clinical evidence will be needed

While scientifically and medically oriented evidence will always be a requirementalways be a requirementIs the priority shifting from efficacy to economic efficiency?A new feature or product must demonstrate superiority over

fthe existing standard of carePre-clinical evidence

Per subject study costs are rivaling per patient study costsPer subject study costs are rivaling per patient study costsTranslation issues from animal models to human modelsFDA’s new emphasis in computational modelingProbably has more of a role in academic research

A Question for IndustryWith the dynamic environment that we are currently in, can we continue to use the existing serial

1. Research2. Development3 Clinical3. Clinical 4. Regulatory

approach that we have traditionally used whenapproach that we have traditionally used when there is

demand from new patients entering the systemdemand from new patients entering the systemand an ever growing cost crisis in the existing healthcare delivery model?healthcare delivery model?

The Randomized Controlled Trial (RCT)Recognized as the gold standard for conclusive evidence generation by scientists, clinicians, regulators,by scientists, clinicians, regulators, healthcare decision makers

Requires at least two groups (treatment and control) with randomizedand control) with randomized assignments and crossoversRequires that the clinicians are blinded to remove bias and deliver objectiveto remove bias and deliver objective resultsRequires rigorous statistical analysis for appropriate design and accuratefor appropriate design and accurate analysis of resultsRequires significant funding, it takes a long time to enroll and followlong time to enroll and followIt has inherent risks to patients, to clinics, to sponsors

The Randomized Controlled Trial (RCT)Challenge 1: Design

Historical “soft” endpoints in many RCTs have led to a debate on the meaning of the resultsgRecent regulatory emphasis on increased power that the RCT can take years to enroll and completeReliance on consistent site to site execution of protocolsReliance on consistent site to site execution of protocols

Challenge 2: Approval and AcceptanceResults are subject peer review by independent panelsRegulatory approval no longer guarantees reimbursementProviders are now being measured on how much they save and the public policy environment could change during an extended RCTWill the initial requirements in a large RCT be acceptable when it has been completed?

Are there alternatives to the RCT?A list of alternatives to explore1. Smaller prospective feasibility research studies2. Larger observational outcomes studies3. Computational modeling as a substitute4 The use of “Big Data” analysis in public databases4. The use of Big Data analysis in public databases5. Mobile devices6 Patient social networks6. Patient social networks7. Automation

Prospective Feasibility Research StudiesWhat are the opportunities?

Smaller prospective studies (n < 100) take less time to enroll and completeenroll and completeCan still have a randomized treatment arm and a control arm with crossoversPatients can be followed for extended periods after the study is completedTh di ti l lt ’t hi t ti ti l i ifiThe directional results can’t achieve statistical significance but those results can still have an impactMore investigators are publishing on their early resultsMore investigators are publishing on their early results

Observational Outcomes StudiesWhat are the opportunities?

Very large retrospective studies (n > 10000) take less time because the data already exists in registries andtime because the data already exists in registries and industry & government databasesObservational and uncontrolled but very powerfulThe results are hypothesis generatingStatistical significance is usually achievedExplanation for the result (Why?) may not be possibleA commitment to publish the study results regardless of its outcomeits outcome

Computational ModelingWhat are the opportunities?

Computer simulations that can be used to model the biological interfacebiological interfaceModels contain a very large number of extremely small elements that virtually duplicate the actual interfaceUse of complex constraints and relations can differentiate between healthy and diseased modelsFDA h t k i d i t t i thi th d lFDA has taken an increased interest in this methodology and spoken in support of it at various academic and industry conferencesyCould save time in the product development cycle by virtually eliminating the need for pre-clinical studies on efficacyefficacy

“Big Data” AnalyticsHow can technology address opportunities?

Consider new sources for data that existConsider new sources for data that exist in very large de-identified patient groups

In Cellular NetworksIn Government NetworksIn Social Networks

Big Data analytics and algorithms couldBig Data analytics and algorithms could provide answers about the forest irrespective of the treesThis concept is a new and growing opportunity

Mobile DevicesHow can technology address opportunities?

Proliferation of healthcare smartphone appsH lth d i k ti t h tHealthy and sick patients have access to many appsThis technology could provide a more consistent execution of clinician trials via mobile appsexecution of clinician trials via mobile appsThis technology could facilitate positive outcomes byenabling patient awareness

Of their risk profilesTrack their health progressIncrease their complianceIncrease their complianceProvide an incentive to stay “healthy”

Patient Social NetworksWhat are the opportunities?

The world of social networking is becoming more popular in the older patient populations that are more likely to bein the older patient populations that are more likely to be sickIt provides a unique opportunity to study patient behavior and complianceIt could create patient groups that share information for the good of the groupthe good of the groupConnection of genotypes to phenotypes?

Automation in the Practice of Medicine How can automation address opportunities?

Current diagnostic equipment is highly t t d d t i i ll i iautomated and acute minimally invasive

equipment is trending towards automationBut not much else isBut not much else isMore automation is on the horizon

Automatic downloading of data with automatic analysisPatients enabling minimally invasive automatic treatments Leading to computers and robots that diagnose and treat patients in-clinic

The Question

Is the RCT becoming a Barrier to Innovation?

Our Goal in this environment should be to develop efficacious solutions that reduce treatment costs on a shorter time-to-market cycle

This Healthcare Environment demands it

The AlternativesThe answer may be found in parallel study strategies as a opposed to traditional and rigorous

i l t d t t iserial study strategies

1 Smaller prospective feasibility research studies1. Smaller prospective feasibility research studies2. Larger observational outcomes studies3. Computational modeling as a substitute3. Computational modeling as a substitute4. The use of “Big Data” analysis in public databases5. Mobile devices6. Patient social networks7. Automation

The AlternativesCardioMEMS: The CHAMPION Trial started in 2007 and has yet to be approvedAn alternative reality1. Conduct a prospective feasibility research study for 6

monthsmonths2. Receive conditional limited regulatory approval 3. Continue to follow the patients from the feasibility study3. Continue to follow the patients from the feasibility study4. Add a much larger pool of patients5. Conduct a retrospective observational study for 1 year6. Receive full regulatory approval in 2 years

ConclusionsThe worlds of healthcare and technology are on a common course

Mobile apps, social networking and Big Data analytics are on exponential growth curvesAutomation algorithms will enable increased clinicalAutomation algorithms will enable increased clinical accuracy with a shorter cycle timeMedical computers and robotics could be morphing into robotic cliniciansPublication of studies using this technology will be used as evidence by non-physician decision makers andas evidence by non-physician decision makers and stakeholders

ConclusionsThe worlds of healthcare and technology are on a common course

The availability of new technology could be harnessed to

h t li i l t i lshorten our clinical trials, enable better outcomes,

th t f t t t f ti t th tsave on the cost of treatment for patients that receive novel therapy

ConclusionsThe worlds of healthcare and technology are on a common course …

The emphasis on economic efficiency may render th d d f f f ffithe demand for proof of efficacy

Obsolete?Unnecessary?Irrelevant?

ConclusionsVinod Khosla bets big on big dataBy Michal Lev-Ram, writer November 13, 2013: 5:48 PM ET

The Silicon Valley startup Ayasdi is just the beginning, the S Mi f dSun Microsystems co-founder says.

"Almost everything doctors know about medicine will be obsolete," Khosla told the audience. Earlier this year, the long-time technologist and co founder of Sun Microsystems led a $10 million funding roundand co-founder of Sun Microsystems led a $10 million funding round in Ayasdi, a newish big data company that utilizes "topological analysis" to look for patterns in massive, often disparate data points. (In plain English, Ayasdi turns mountains of linear information, like what is found in health records, into geometric shapes that people can interact with.) The Palo Alto, Calif.-based company is one of an exploding number of big data start-ups. But while most companies' offerings rely on data scientists to query systems with questionsofferings rely on data scientists to query systems with questions, Ayasdi says its approach enables companies to glean insights they didn't know they were looking for. General Electric, Citi and Merck are among the company's early customers.