Big pharma companies have become more cautious in their risk taking, with mergers and acquisitions gradually giving way to joint ventures and partnerships.
When COVID-19 wreaked havoc on our markets, biotech looked like an outlier, not only weathering the storm, but coming stronger than ever with record investments and valuations . Then reality hit, leaving assets in the early stages.
Commoditized products underperformed, valuations plummeted, and the new normal arrived. This has created a paradox for SMEs as to how they can offer not only promising innovations but also low-risk investment options in an increasingly cautious market.
Even before the pandemic, small to medium-sized biotech companies hoped to overcome faster adoption of new technologies, faster-paced innovation, and internal stagnation to offset impending patent expirations. It had gained a position thanks to its partnerships with large companies.
EY reports that approvals of new molecular entities (NMEs) attributed to small biotech companies with less than $1 billion in revenue were around 10% in 2017 and will reach 30% by 2021 has been reported to have Late-stage asset development remains flat, but is up to 50% faster than before through early-stage testing.
The eventual market downturn meant biotech had to take an unfamiliar path toward commercialization or prove its worth to increasingly fearful investors. Today, large pharmaceutical companies are becoming more cautious in their risk taking as mergers and acquisitions are increasingly being replaced by joint ventures and partnerships.
Investors are reluctant to jump early, often delaying the move until after Phase 2 or 3 trials, demanding data-backed validation and setting rigid milestones. Biotech companies with early stage assets or platforms can no longer take the easy path to an IPO and instead face increasing demand to differentiate themselves in a sea of similar start-ups. increase.
Many companies are waiting for the recession to subside, stretching budgets and streamlining operations while remaining as private as possible. Some companies have curtailed their R&D efforts or joined a number of competitors focused on indications with well-validated assays and endpoints. This is a strategy that we fear could stifle innovation in the long run.
Rapid innovation with good returns in the face of a myriad of other challenges such as declining late-stage assets, rising consumer expectations, new pricing laws, and increasing cyber threats for many biotech companies Achieving a seems like an insurmountable task. To meet market demands, companies must adjust their strategic priorities.
Deloitte recently reported on key priorities for biopharmaceuticals to remain competitive. Aside from expanding global reach, strengthening R&D and improving the use of digital and IT technologies was cited as a top priority.
Investing in a scalable R&D platform
As biotechnology grows, systems that once sufficed for small teams typically don’t scale well and start to hinder progress. Companies are faced with the choice of building an end-to-end chemical information discovery platform on their own or finding a partner who provides an open platform that helps them seamlessly integrate the diverse applications, workflows, and data they need. I’m here.
Adopting a flexible and scalable R&D platform reduces the burden of integrating internal systems such as those used for study capture, compound registration, inventory management, assay design, and data management. Companies can focus their time, money and expertise on what matters most: the science that helps them develop better treatments faster and increase their chances of success.
Supporting transformational change
Biotech companies need to analyze their R&D workflows and identify changes that not only affect the processes of some teams, but also improve the performance of the organization as a whole. A key priority for many drug discovery companies should be investing in technology that allows decision makers to focus on science rather than tedious processes.
Unfortunately, several obstacles hinder this goal, including fragmented R&D systems, workflow complexity, declining data value, high failure rates in small molecule drug discovery, and structural complexity and diversity in biologics discovery. often become Companies can overcome these obstacles by investing in tools that streamline end-to-end workflows, accelerate research, foster collaboration and improve decision-making.
Create a strong data foundation
Big data has become synonymous with great potential. Companies in various industries are looking to both gain a competitive advantage and generate revenue.
It also pours tens of millions of dollars into AI initiatives each year. Unfortunately, many biopharmaceutical companies face a harsh reality. Data are unsuitable for use in AI for a variety of reasons, including poor access, lack of standardization, inefficient annotation, questionable completeness, and limited traceability.
In fact, a recent Deloitte survey of biopharmaceutical and medtech companies found that nearly 30% of life sciences leaders admitted their data struggles were negatively impacting their AI initiatives. understood. Biotech companies need to build a strong data foundation to benefit from AI and machine learning. This means getting clean, authoritative research data, removing data silos, and provisioning model-quality data.
Efforts to comply with regulations
An increasingly common regulatory issue facing leaders is data integrity. This can have a significant impact on drug safety, efficacy and quality. Such violations have become more common as labs move from paper record keeping to electronic record keeping, and the FDA has released industry guidance on the issue.
Vicious crimes such as data tampering have made headlines, but the FDA’s transparent sharing of warning letters has resulted in data loss, missing metadata, deletion or reprocessing of uninvestigated samples, and security risks. Security issues, improper audits, and more crimes have grabbed headlines. Fortunately, labs can choose solutions that help reduce the risk of breaches, such as automatically recording experiment details and audit trails, requiring signatures, and restricting manipulation or deletion of data. .
Maintaining the integrity and security of the data generated throughout a product’s lifecycle can help ensure regulatory compliance and make the product more attractive to investors. . Biotechnology faces new challenges, but history shows that the industry has always recovered.
McKinsey predicts the market will recover if companies carefully focus their talent and budgets without losing sight of fundamentals. This will provide regulatory clarity for innovative therapies that address unmet needs, increasing their potential for commercialization.
About the author
Haydn Boehm is Director of Product Marketing at Dotmatics, a leader in R&D scientific software that connects science, data and decision making. Its enterprise R&D platform and scientists’ favorite applications increase efficiency and accelerate innovation.