Fundamental Shifts In Business Models Are Looming For The Biopharma Sector That Will Determine The Next Generation Of Winners And Losers

The biopharma industry will look very different in the next several years.  While biopharma players will still continue to produce and market drugs, their fundamental business models, value proposition, how they organize themselves and go to market will change dramatically.  They will start to view themselves as information and digital solution players rather than suppliers of pharmaceuticals and or medical products. They will be providing “solutions” to payors, providers and patients that improve outcomes, lower costs and ultimately enhance quality of life of patients.   Just providing the therapy and continuing patient support will not be enough.  Pharma will need to adopt new approaches beyond the pill, leveraging modern technologies to ensure that the right patient gets their therapies at the right time in their journey and that they stay on therapy at the required dose while minimizing adverse events.  Several forces are at play that are forcing biopharma and other healthcare players to rethink their value proposition:

  • Advent of value based care in US and EU
  • Growth of novel precision med approaches beyond genomics  to “omic” biological signatures,  phenotypic and behavioral data and the emergence of new types of targeted therapies
  • Digitization of medical records including pathology and radiology images
  • Emergence of AI, machine learning and big data technologies
  • Decentralization of healthcare and patient centered-ness (including increasing patient empowerment.)

Value based care is already here

More than 50% of oncology clinics in the US and a higher percentage in EU are under value-based contracts.  OCM[1], MACRA/MIPS[2], are just few US examples of new programs in oncology that have demonstrated varying degrees of success.  These are designed to alter the incentives of hospitals and clinics (and pharma) so that they are aligned in improving patient outcomes and quality of life.  In May 2016, ASCO published guidelines on how to assign value to new cancer therapies based on efficacy, toxicity and costs. While providers have embraced value-based care, pharma and medtech players have been woefully behind and are increasingly under pressure to move in this direction. At the same time, there have been significant developments in Precision Medicine with increasing amounts of data being generated on patient samples along with novel data integration and analytics approaches.  Innovative pharma have adopted these novel data-driven approach to identify novel drugs, targets, their MoA and associated biomarkers and hence are able to reach the market much faster than any of the incumbents.

[1] Oncology Care Model

[2] Medicare Access and CHIP Reauthorization Act/ Merit-Based Incentive Payment System

Emergence of big data, precision medicine and outcomes-driven models

In cancer, most late stage patients undergo testing that generates gigabytes of data including full genomic/ transcriptomic profiling, high dimensional imaging, flow cytometry, cytokines and patient reported outcomes and behavioral data.  Precision med is moving from single biomarker to complex “omic” signatures and even image analytics as highlighted by players such as and new biotechs such as Recursion.  Given these changes, the pharma and most of the medtech industry will now be building capabilities to leverage precision and big data approaches to improve outcomes, lower costs and improve quality of care and will be held accountable for demonstrating tangible results to ultimately improve patient care! These players will have to shift to new ways of engaging physicians, patients and payors.

Gone will be the days where success depended solely on the performance of the drug (or the med device).  The new game will need a much different value proposition where the basis of competition will shift from the product to the “solution” that positively and measurably impacts patient outcomes and quality of life.

Emergence of New Business Models

How will the biopharma model change and what are the implications for the industry?  Here are some examples across the entire value chain:

  • Outcomes-based or “value-based” contracting: Drugs will generate revenue based on reaching certain milestones on patient outcomes and quality of life
  • “Beyond the pill” solutions (or beyond the device or diagnostics): Move to providing differentiated services including digital intervention, management
  • Innovative means of physician engagement and decision support: Deep integration into the hospital information networks to be able to map the entire patient journey and identify patients and intervention earlier in their journey
  • Innovative patient engagement: real time patient management and support: monitoring patients on a proactive basis including biomarkers, phenotypic data, behavioral data, patient reported outcomes etc. to enable early intervention in case the drug does not work or there is an adverse reaction from the drug. This will be the new definition of “precision medicine”
  • Novel “precision” approaches to identify and pre-select patients; move from companion diagnostics to AI/ML algorithms based on multi-omic signatures
  • Early Intervention in Patient Journey: The healthcare industry has limited visibility on patient journey due to fragmented nature of care. Pharma and medtech players are no exceptions to this rule. Going forward, whoever owns the VISIBILITY on patient journey will have a leg up over competitors
  • Data as a weapon: providers and pharma will develop new mechanism to access and mine patient data across the journey in a secure and compliant environment which be used to create new drugs, secure access and pricing.
  • Real world evidence to gain market access: Clinical trials will not be enough to gain full approvals on novel therapies; pharma will have to develop new systems to monitor patients in the real-world setting.
  • Value pricing and tender process leveraging advanced data management: akin to the airline industry, pharma pricing will be based on regional nuances on patient satisfaction and outcomes impact: this implies that the industry will have to be able to monitor outcomes on a near real time basis.
  • Innovative “Precision” Clinical Trials: With growth of multi-omic precision biomarker data, there will be a need for advanced data ingestion, interrogation and analytics technologies based on AI/ML with data being monitored throughout the trials. Trials will become patient centric rather than site-centric trials. more and more patient samples will be taken at increasing frequency and deep biomarker interrogation will be performed based on “omics” other phenotypic measures that closely monitor patient response to therapy; novel automated methods for patient recruitment will emerge.
  • Innovative Early Discovery: heavy use of AI and ML to discover biomarkers (targets and biomarkers to monitor efficacy and predictive response), which also implies that there will be heavy precision biomarker data generated with AI and ML technologies (e.g. Berg as well as Recursive Pharma are already taking this approach.
  • Emergence of novel and highly potent therapies: We see a shift in R&D to novel highly potent therapeutics modalities that promise high efficacy in small doses. These include not only DNA/RNA, Gene therapies, peptides, antibody drug conjugates but also new forms of small molecules (e.g. Protacs); these modalities will require innovative methods for R&D.
  • Digital Channels: new Amazon-like Direct to Patient channels are likely to impact the distribution chain with price transparency, lesser markups and faster deliveries. This is one of the major bottlenecks in the industry as even life-saving drugs take on average 6 weeks for delivery!
  • Small volume batches: novel manufacturing and logistics processes for small volumes and batches with the emergence of high potent therapies.
  • Innovative and Non-Traditional Alliances:  We are likely to witness many non-traditional alliances between pharma, medtech and information solution providers.  This means that the entire BD and competitive intelligence functions will have to evolve.

Implications for Biopharma (as well as MedTech players)?

All of the above forces will require pharma and other healthcare entities to develop new capabilities which includes new systems, processes, with new skill-sets as well as instill new change management practices into their organization so that they can successfully adapt to and manage this dramatic and disruptive change in business model.

Who is Zaylan?

We have developed a novel approach to developing strategic direction and concepts related to digital solutions in order to cater to this new world of precision data and value-based care.  Our goal is to enable healthcare industry participants to develop capabilities and control points that will allow them to dramatically improve outcomes, lower costs and increase quality of care.  We are a group of world class strategists with a strong expertise in life sciences as well as professionals with deep technology expertise from Silicon Valley that have deployed digital solutions.  However, unlike traditional strategic advisory, we focus on solving emerging problems and generating novel business models by leveraging modern technologies.  Moreover, we have strong technology and execution capabilities allow us to deploy solution concepts to market rapidly. We have partnered with tech companies that have expertise in deploying digital solutions in the healthcare space (see example– INDx and Parker Inst).   We also recognize that change is not just about strategy and technology but all about instilling the right set of processes, incentives and a strong top down vision. Zaylan has developed a unique approach to change management in the digital age.  Here are key strategic services offered by Zaylan:


  • Strategic audit of current digital and precision capabilities
  • Patient journey analysis and unmet needs; value pool analysis
  • Problem identification and business case
  • Capability and gap analysis
  • Evaluation of potential partners to address gaps (we have a database of emerging innovative players that are developing modern technologies)
  • Competitive review of digital players

Early Experience Studies:

  • Rapid prototyping and piloting
  • KPIs to measure impact on outcomes
  • Back-end integration, useability and design
  • Business model design

Change Management Support:

  • New processes, skills and incentives needed for digital solution models; BD opportunities identified
  • Organizational alignment across the entire organization from global to regional and country levels
  • Manage and monitor KPIs and adjust accordingly

Contact: Arshad Ahmed,