A: There are multiple challenges that remain. The estimated cost to develop a diagnostic not linked to a medicine from a company with an existing infrastructure is approximately $65m not including commercial launch costs. That magnitude of investment requires and merits a transparent path to reimbursement at the value the diagnostic brings to the targeted clinical utility rather than simply the cost to literally perform the test Lastly, there must be an increased understanding of the rigorous and costly path of a diagnostic discovery from ‘research-grade’ laboratory test applied to opportunistic sample sets to a ‘clinical-grade’ assay supported by quality evidence when wisely integrated into patient management to improve outcomes.

A: The adoption of a clear diagnostic development path analogous to Phase I-III for medicines was developed only relatively recently. In addition, several professional organizations have made a Herculean effort to embed best practice recommendations into diagnostic guidelines. We must familiarize the healthcare community with the phases of diagnostic development and encourage use of these guidelines. The phases of diagnostic development include Analytical Validity, Clinical Validity and Clinical Utility followed by Health Economic support for improved outcomes. Some of the important key elements of this pathway include rigorously characterized and locked ‘clinical-grade’ assays, separate training and validation cohorts that are identical to the planned ‘intended use’ application and validation of the test by the laboratory staff who will carry out the test in the dedicated laboratory. Also, patients do not have the time to await an ‘Exploratory Walk’ of development sometimes used by those interested in innovation in diagnostics; we need to follow a ‘Directed Path’ for translation to be timely and cost-effective. And we must understand that a commitment to evidence is more nuanced than simply asking whether a randomized controlled study was performed. Prospective collection of evidence from multiple centers analyzed using pre-specified statistical analysis plans may be sufficient for some diagnostic applications.

A: Precision Medicine promises the use of the right medicine and/or diagnostic at the right time for the right patients with quality evidence that provides a high level of confidence that lives will be extended, quality of life will be improved and healthcare will become minimally more cost-effective and maximally cost-saving. Clinical genomics, not unlike other healthcare interventions, must collect quality evidence for specific actionable clinical utility but this requirement appears to be challenging to achieve and has been underappreciated by some in the community.

A: The clearest demonstration of value of clinical genomics applications is when care is accelerated to subsets of patients with a clear unmet clinical need to intervene using standalone or paired medicines and diagnostics that extend survival and improve quality of life in a cost-effective manner. Clinical genomics must be part of the solution to the ever-increasing cost of healthcare. The focus has to be not only on the introduction of innovative medicines and diagnostics but also must assist in avoiding unnecessary or ineffective therapies as well.

A: With the transition from fee-for-service to fee-for-value diagnostics, we need to be cognizant of health economic studies that reach so far into the future that value-based care becomes onerous to annual budgets. Valuation should take into consideration the time horizons of health economic studies so as not to strain stressed near term budgets. Innovative health economic solutions are needed here. Further, CMS plans to reimburse episodes-of-care recognizes the importance of forecasted longitudinal test use.

A: Hans Eichler at European Medicines Agency pioneered and continues to develop an approach referred to as ‘Adaptive Licensing’. This approach balances timely access for those patients with a disease that benefit more and risk less if an innovative medicine or diagnostic is used. Other patients with same disease but potentially may risk more and benefit less requires additional evidence before using the same medicine or diagnostic. Even though in past, ‘Adaptive Licensing’ has referred solely to medicine regulatory review, the strategy is equally applicable to diagnostic regulatory approval and reimbursement.

A: I expect three key take home messages. Attendees will i) understand the foundational achievements that clinical genomics has already contributed to Precision Medicine with increased survival and improved quality of life of patients, ii) hear about exciting progress in disease-specific and disease-agnostic technologies that continue to unfold and iii) appreciate that much still needs to be accomplished if we are to impact the lives of even more people. I am particularly excited about the complementarity role of organ/tissue imaging and noninvasive blood-based tests to shed new light on disease stage and treatment response.

A: We do not have a level playing field for a company insightful enough to commit to high quality evidence first-in-class intended use. Upon completion of quality evidence studies, other diagnostic companies can relie on that data for reimbursement even though their tests have not been demonstrated to perform at equivalent levels. Payors should recognize and support first-in-class tests. We owe it to patients to reimburse tests that have demonstrated rather than inferred performance. If medicines have exclusivity to protect investment of innovation shouldn’t diagnostics?

A: As usual, the agenda looks excellent with many informative talks by leading domain experts. Rather than identify specific talks, there are four underlying themes that I would encourage attendees to keep in mind as they peruse the meeting schedule. First. AI and Data Science driven Healthcare presentations promise improved disease and health management by integration of electronic medical record data and diagnostic test results. Even though the ultimate objective is unsupervised self-learning algorithms, locked semi-supervised, interpretable machine learning algorithms will be critical initially. Second, attend presentations that discuss value-based care that emphasize the role to be played by reimbursement to encourage and reward commitment to innovation and quality evidence to ensure the quality healthcare engine thrives. Third, track the genetic and genomic informed care presentations which are the keystone of Precision Medicine, timely, patient-stratified, evidence-informed care. Fourth, attendees should review the agenda to attend sessions that span discovery to implementation to understand present patient management advances that are being implemented as well as technologies, information and knowledge with rich future potential. Lastly, we have assembled an excellent reimbursement panel with diverse and extensive payer experience including Steve Anderson (LabCorp/Covance), Gabriel Bien-Willner (Palmetto GBA), Bruce Quinn (Quinn Associates), and Susan Xu (AAMC) that I expect attendees will find particularly informative.