In this first installment of our molecular biology series, we’ll discuss the importance of scientific and technological evolution in the R&D space.
A new era of breakthrough science is reshaping the healthcare, biotech, and agricultural industries. The scientific approach to treating patients, fighting emerging disease, and conquering world hunger has been transformed by molecular technologies that allow scientists to manipulate and edit the genome, dissect metabolic disease, and digitally characterize treatment efficacy.
Advances and discoveries in genomics and other frontier sciences, collectively known as the “omics” (a group of biology disciplines whose names end in the suffix -omics, such as proteomics, metabolomics, metagenomics, etc.) have enabled the development of personalized medicine, rapid vaccine development, and sustainable agriculture for a changing environment.
Molecular Biology: An R&D Foundation
Molecular biology can be thought of as the R&D foundation for a range of industries, from biopharma and biotechnology to agricultural science and vaccine development. Investment in R&D is at an all-time high.
- The top 20 pharmaceutical companies are set to spend approximately $60 billion on drug development each year.
- The biopharma sector is spending an average of six times more in R&D as a percentage of sales than all other industries combined.
- The average cost of bringing a single drug to market now around $2.6 billion.
With the massive investment in biopharma R&D, one would think bringing novel drugs to market was a successful venture. In fact, after 10–15 years of development and billions invested, only 12% of new molecular entities that start clinical trials actually make it to become FDA-approved treatments for disease.
The Need for Robust R&D
Although drugs may fail in early-stage R&D for a multitude of reasons, failures are also common during late-stage development and clinical trials as a result of undocumented toxicity or lack of efficacy. Still others, which may otherwise be excellent therapies, fail during the Investigational New Drug (IND) application process because of inconsistency in R&D testing or a general lack of supporting data 
evidence provided to the FDA. Losing a drug in early-stage development is a natural and accepted part of the R&D process as multitudes of compounds and therapies are screened and tested against one another. By contrast, a late-stage failure can be devastating to even the strongest pharma company.
At their core, R&D investments yield critical technology from which a company can develop new products and services. But for R&D to deliver genuine value, its role and data must be centrally woven into the organization.
Unfortunately, many enterprises lack an R&D strategy that has the necessary agility, data capture capabilities and robustness to realize the organization’s aspirations. Instead of serving as the company’s innovative engine, R&D can end up isolated and disconnected from leadership and quality management, out of sync with necessary oversight. This increases unnecessary expenditures, reduces efficiency, and may even cause catastrophic late-stage R&D failures.
Companies wishing to stay ahead of competitors need a robust R&D strategy that makes the most of their innovations, speeds time to market, and eases the transition through hurdles helping them reach development milestones. A key part of making this strategy work is determining ways of reducing unnecessary costs and losses while enabling the innovation and collaboration required to succeed in today’s fast-paced world.
Biopharma has some of the highest R&D-related costs of any field. It’s also fighting an uphill battle, because at its core almost all molecular biology involves overlapping networks of omics-related technologies. In-depth sequencing may be required to find relevant allelic variants with both known and unknown effects before relevant therapies can even begin to be designed.
Harnessing the Power of Biological Data
Easy access to complete genomic information may eventually cause a shift in regulatory approaches when considering the approval of new drugs and diagnostics targeted at rare mutations and personalized medicine. As a result, the field of molecular biology is developing a growing reliance on software simulation and automation technologies such as artificial intelligence-driven predictive approaches, digital biology, blockchain, nanotechnology, 3D printing, robotics, extended reality and a plethora of others.
Big data pipelines – and the use of predictive modeling of biological processes and drugs – are becoming widespread as a result of R&D organizations using more diverse sets of molecular and clinical data.
Machine learning and advanced analytics allow data mining across ever-increasing data sets, enabling scientists to understand and visualize drug interactions with targets and to predict in silico a molecule’s likelihood of success before a single pipette has been hoisted at the bench.
This has a profound benefit on the ability of manufacturers to identify molecules with the highest probability of successful development, and the reciprocal benefit of identifying failures earlier in discovery and development. Clinical trials could also be smaller, shorter, less expensive, and generate better insights.
However, biopharma R&D often lags when it comes to digital transformation efforts due to:
- concerns about lack of compliance with regulatory groups
- data consistency and integrity
- pipeline changes and slowdowns
- lack of digital talent
- insufficient understanding of digital data topics and implementation.
4 Keys to Successful Change
Our experience with companies inside and outside biopharma suggests there are four core principles for succeeding with this kind of all-encompassing change program:
- First, R&D organizations need to identify and prioritize their critical sources of value — those capabilities that impart competitive differentiation, but also those that would benefit most from digitization.
- Second, they must build their delivery engines, not just managing new digital technologies but integrating with agile data science on a basic level.
- Third, R&D companies must look for ways to modernize their IT foundations, such as moving to cloud-hosted digital platforms delivering software as a service (SaaS) – allowing the organization to manage their own data as a strategic asset without having to worry about the containers holding that knowledge or the security protocols protecting it.
- Finally, companies must ensure that they build and maintain core management competencies which allow them to pursue a successful digital agenda.
Within biopharma R&D, these technologies present an opportunity to ensure better outcomes for patients via targeted therapies while significantly reducing the cost of drug development and accelerating time to clinic.
The LabVantage Advantage
Utilizing LabVantage as your digital partner can help ease your digital transition or provide better ways of storing and accessing your molecular R&D, clinical biobanking, and manufacturing data. LabVantage offers a comprehensive and fully validated pharma package in both a cloud-hosted SaaS model, advanced APIs, and instrument interfaces.
For biopharma, biotech, and agriscience R&D groups, LabVantage Solutions will be releasing a molecular biology suite coupled with our advanced ELN and fully supported by our industry-leading LIMS. Contact us today to learn how LabVantage can help you design the results-driven metrics, collaborative tools, and consistent data storage necessary to help you organization develop, test, and manufacture your next product.
