By G. Botsakos, N. Saward, and A. Berman, PA Consulting Group
Over the past 20 years, biopharmaceutical companies have focused on driving out costs, accelerating timelines, and driving compliance. Yet, results have stagnated. We have seen a steady decline in pharma R&D productivity1 while other industries continue to make further progress with respect to simplification, innovation, and growth.
In 2017, we witnessed increased competition, sweeping regulatory changes such as General Data Protection Regulation (GDPR) and the evolution of Policy 0070, a tumultuous geopolitical landscape, scrutiny over drug pricing, and increased R&D costs. Although the biopharmaceutical industry continues to grapple with scrutiny over drug pricing and likely will for some time, U.S. approvals actually doubled in 2017.2 Due to eased regulations by the FDA for novel therapies, companies could focus on personalized medicines and rare diseases, allowing the initial wave of gene therapy to reach the market.
While the primary concern is bringing the best therapies to patients, biopharmaceutical companies are also challenged by a competitive landscape. The global oncology market is expected to hit $120 billion by 2020,3 with increased opportunities to bring immunotherapies and other oncology medications to market. Additionally, the launch of type 2 diabetes products continues to be a priority for biopharmaceutical companies in 2018,4 and this year will likely see the launch of highly anticipated drugs designed to treat HIV, migraines, and multiple sclerosis.5 It is this competitiveness that drives the need to find more innovative ways to accelerate development programs and understand the landscape.
As we look further into 2018, tax cuts and repatriation of foreign cash reserves could spur a wave of M&A activity to further boost pipelines and portfolios. Innovative therapies and better insights from increasingly diverse data sets will continue to be a strong focus for organizations to drive this growth. Organizations will look to leverage simplification, advanced analytical capabilities, robotic process automation (RPA), and artificial intelligence (AI) to increase productivity and help accelerate products to market.
To propel their businesses forward and ensure they stay competitive, companies should consider four key strategies:
1. Accelerate products to market through the use of data, analytics, RPA, and AI.
After over 20 years and thousands of internal optimization initiatives, companies have not seen a sustainable and marked improvement in operational performance of key R&D processes, most notably clinical trial planning and conduct, where more than 70 percent of studies run behind schedule and even more finish over budget.6 Companies have begun to look to emerging technologies such as AI in their search for more innovative ways to accelerate development programs.
The growth in the use of digital technologies has created new data sets available to be mined for insights. This has allowed companies to refine therapies, identify digital biomarkers, and discover new possibilities to more efficiently identify patients and sites. Companies will look to Big Data technologies to integrate these data sets and take advantage of more advanced data analytics capabilities to uncover the hidden messages that the data can provide.
In order for companies to shift to this world of patient-driven design and digital capabilities, they will need to focus on automation, robotics, natural language processing, and the use of neural networks to maintain and accelerate the development timelines. These technologies will allow integration of unstructured and structured data sets, processing of new types of data, generation of insights, identification of the right sites and patients, automation of study start-up, processing of study reports for submission activities, and easier, more efficient safety case processing and decision making.
To date, we have been disappointed with the promised change and value AI should be delivering. In 2018, companies will define robust strategies (“Think Big”) around AI and look for targeted opportunities (“Start Small”) to leverage AI and real-world data to make progress and allow agility to scale these successes.
2. Focus on differentiated medicine, therapies, and outcomes.
Patients are more in control of their treatment than ever before. There is greater awareness of possible treatment options, which is enabling empowerment and the ability to drive decisions regarding individual treatment. Earlier this year, Amazon, Berkshire, and JPMorgan announced a partnership that aims to improve healthcare options available to their employees,7 which will in turn disrupt the healthcare industry. Consumers and patients will continue to drive this and similar changes as they demand new and efficient treatment options.
Companies are beginning to and need to continue to respond to this paradigm shift by continuing to evolve their patient engagement strategies, including developing patient-centric and patient-driven trial designs and capabilities. The emergence of digital capabilities is driving the ability to engage directly with a more educated patient and design development programs with patient well-being and outcomes at the heart.
Consider this: you have a chronic asthma patient who requires quick-acting inhaler treatments that open up airways during an attack. A connected inhaler that sends “real-time data regarding the duration of inhalation, amount of inhalation, and location of use” can help the patient and caregivers quickly understand how well the patient is adhering to the assigned treatment regimen.8
The development of apps and innovative digital solutions such as this will enhance patient care and help grow the market for biopharmaceutical companies that are able to capitalize on the available technology to stay ahead of the curve.
Increased understanding and focus on patient needs, paired with technology innovations to enable better monitoring and diagnostics, will position biopharmaceutical companies to deliver against desired outcomes. Additionally, it will be crucial to understand positioning and value of these solutions and services across populations and geographies to drive market access and acceptable pricing models.
3. Transform technology and data capabilities.
Many biopharmaceutical companies are continuing to evolve to become data organizations — for drug submissions, to optimize sales, and to drive decision making. Their ability to capture and manage data, integrate new data sources, generate insights, and drive engagement will continue to be a competitive advantage for the foreseeable future.
They need to rapidly adapt to changing compliance and regulatory requirements, to protect their data from increasingly frequent — and sophisticated — threats, and use technology to drive productivity gains and ensure that their internal technology capabilities can scale appropriately to meet evolving needs.
While good progress is being made by some organizations on their preparations for Europe’s General Data Protection Regulation (GDPR), awareness generally seems low, and many biopharmaceutical companies are still trying to understand the magnitude of work required to comply with the regulations around internal governance processes to manage data and technology. For this reason, we anticipate feverish work in this space throughout much of 2018 … even after the May deadline passes.
With a number of well-publicized incidents, 2017 highlighted that many companies, including Big Pharma, are vulnerable to cyberattacks, and the costs of not being prepared can quickly run into the hundreds of millions of U.S. dollars. We expect to see much more focus on security and the CIO function as a result.
Most medium-to-large biopharmaceutical companies already use agile methods in pockets, typically for IT work. However, restricting agile to the IT function caps the value that can be achieved — the reason agile works as an IT concept is equally applicable to other parts of the business. It also means that IT is missing out on an opportunity to influence and educate the wider organization on a proven technique for driving productivity. AstraZeneca has just announced a four-fold increase in R&D productivity in the 2012 to 2016 period over what it achieved in the period 2005 to 2010, and while it is no doubt due to many factors, perhaps it is also no coincidence that AstraZeneca established a strong agile culture across the organization during the recent period.
While there are many other technology and data trends, recruiting in-demand skills to address these needs will continue to be challenging. The job market is buoyant and technologies are changing rapidly. For this reason, we expect that IT functions will continue to evolve to manage collections of services and push the recruitment problem onto vendors. This will have implications on the skills required in-house.
4. Drive simplification and compliance into the business.
Regulatory uncertainty continues to dog biopharmaceutical companies, given the recent attention to drug pricing concerns. For industry leaders to remain compliant with changing regulatory guidance, companies must be prepared to respond nimbly to emerging local and global regulations to drive cost and risk out of their organizations.
To achieve this, companies should take stock of their compliance and regulatory systems in an effort to simplify the processes/SOPs, ensure operational excellence through a “cost out” analysis, and have a firm grasp of the current and emerging regulatory requirements in place across all business domains, including R&D, commercial operations, manufacturing, and enterprise functions. Companies are also beginning to look at holistic designs to build compliance and quality into their processes to allow them to nimbly meet expected regulations and avoid one-off solutions.
For example, some leading companies evaluating GDPR and EMA Policy 0070 considerations anticipate similar regulations in geographies such as North America. Rather than investing in multiple large programs to address those requirements, these companies are looking for modular ways to treat their internal data, both structured and unstructured. Some are also applying “quality by design” principles that have been prevalent in other areas, such as manufacturing, to their businesses.
Similar to the other business aspects discussed previously, we expect companies to continue to leverage data harmonization strategies, predictive analytics, RPA, and AI to obtain early visibility to new regulations, understand and evaluate the impact of these regulations on their current practices, and monitor the biggest areas of risk for their businesses.
We will see more “risk-based” approaches similar to risk-based monitoring (RBM) used in areas such as proactive surveillance of adverse events. These technologies will also be used to better control dossier change management, labeling updates, commitment tracking, and even understanding the impact of historical responses on regulatory approvals and timing.
The industry will see a mixture of new emerging trends and an evolution of historical trends heavily influenced by technology innovation and AI. 2018 promises to be an exciting year that will strengthen the position of some existing leaders and elevate some new companies focused on building forward-looking platforms that will deliver future innovation and growth. Those that do not respond will become less relevant in a growing competitive market.
About The Authors:
George Botsakos is the global life sciences lead at PA Consulting Group focused on helping clients define and deliver high performance and innovative strategies. He brings a deep understanding of the life sciences business, trends, and emerging capabilities based on working with many of the top 20 pharmaceutical and biotech companies for over more than two decades. Connect with him on LinkedIn.
Neil Saward is a life sciences expert at PA Consulting Group focused on managing complex technology programs. He helps clients to innovate and transform the way that they do business by leading the architecture, evaluation, and deployment of new technologies to ensure that the right solutions are implemented, providing technical assurance to ensure that the programs deliver upon their goals, and driving the adoption of agile to help companies deliver IT programs more faster and more effectively. Connect with him on LinkedIn.
Adam Berman is a life sciences expert at PA Consulting Group focused on helping clients design and deliver innovative strategies to accelerate product development programs. He brings a deep understanding of the product development life cycle and has worked with most of the top 20 pharmaceutical and biotech companies to implement new capabilities across the entire R&D value chain. Connect with him on LinkedIn.