Data is a commodity across all life science companies, serving to help drive an organization’s strategic direction and helping to understand what has and has not worked in the past. With the increased emphasis being focused on the variety of uses of data in day-to-day business operations, here are some reasons why it can be so important to implement for pharmas and biotechs.
Accelerate the Research & Development Process
The R&D process is key to both pharmas and biotechs alike, starting with basic research and drug discovery stages before ideally culminating in approval by government agencies such as the EMA or FDA. With this in mind, the ability to quickly search through the data included in the likes of clinical trials, patents and scientific publications can prove to be a more efficient way for researchers to analyze previous test results. Combined with predictive analytics, this can also allow organizations to devise potential approaches to developing a suitable asset for market. The utilization of data and analytics in the R&D process can also aid in reducing costs. Seeing what methods had previously proved to be unsuccessful for other researchers can thus minimize the time and, in turn, the costs needed to carry out clinical trials.
Many big pharma organizations are open to sharing data from their previous clinical trials with researchers, as exhibited by companies such as Pfizer and Merck.
Optimize Clinical Trials
Clinical trials are costly endeavors, with Phase 1 studies reaching up to USD 6.6m, with expenses only increasing in subsequent trials. Having patients with the correct factors to participate in the study is a crucial aspect of conducting the trial to ensure optimal results and to lessen the chance of an unsuitable candidate being involved in the research process. In this scenario, big data can aid in identifying the appropriate patients by analyzing datasets such as their demographic and historical data and implementing machine learning technology to decrease the need for manual intervention, leading to both cost and time-saving benefits in the clinical trial process.
Assessing Potential Partnerships
Data plays a vital role in evaluating potential partnerships within the pharma and biotech sectors. By analyzing clinical trial results, intellectual property portfolios and financial health, companies can identify partners that align with their strategic goals. For instance, a biotech firm may use data to assess a pharma company’s success rate in bringing similar products to market, ensuring a good fit for collaboration. Additionally, competitive intelligence data can help gauge a potential partner’s market presence and reputation, reducing the risk of alliances with companies that may not deliver on expectations. This data-driven approach ensures that partnerships are built on a solid foundation of shared strengths and complementary capabilities, leading to more successful and sustainable collaborations.
Greater Insights into Sales, Marketing and Business Development
Pharma and biotech assets are constantly facing competition, especially with generics. Here, sales and marketing play an important role in encouraging the use of the organization’s products and finding a point of differentiation to separate themselves from their competitors. Data can play an important role in this department, such as in identifying new niches and markets to operate in with the aid of a variety of data sources such as electronic medical records and scraping social media websites.
In tandem with this, the same approaches can also be utilized to obtain feedback on the company’s products and analyze consumer behavior. This analysis can then be implemented when constructing marketing campaigns and advertisements to reach out to the relevant consumer segment and appeal to their needs.