Pharmaceutical R&D has witnessed a decline in productivity over the past two decades. The ever-increasing costs of development combined with increasing challenges to growth and profitability are just a few reasons why progress has stagnated. However, due to the increasing use of big data in pharmaceuticals, this appears set to change. Big data enables companies to obtain and analyse datasets from a wide range of sources. This in turn allows them to identify new drug candidates and define more innovative strategies for drug development. The benefits that are being seen by pharmaceutical companies who have incorporated big data is changing the mindset of the pharmaceutical industry to become more accepting of the use of such advanced technology in medicine. Below are just a few of the ways big data is transforming pharmaceutical research and development.
Predictive modelling and development of new drugs
Big data enables scientists to take more intelligent and sophisticated approaches when analysing and identifying potential drug candidates. The vast amounts of clinical and molecular data that is analysed combined with advanced modelling techniques allows for the identification of compounds that have a high chance of being successful if developed into a drug. Analytics in medicine now allows for the ability to combine and process data from different sources such as genomic sequencing, medical sensors, and electronic medical records, meaning more personalised and targeted medicines can also be developed. The exact cause of specific pathologies as well as predictions of how different patients will respond to the potential drug can also be identified.
More efficient and streamlined clinical trials
Clinical trials are a long and costly part of pharmaceutical R&D that come with high risks of delay and error. Big data is alleviating common challenges faced in clinical trials and evolving them into more effective, streamlined, and cost-efficient processes.
As big data enables the analysis of a wide range of datasets, information from sources such as social media, not just doctor’s visits, can help to identify more eligible participants. Even participant criteria for trials is expanding as genetic information, disease status and other individual characteristics can be used to identify a niche set of patients for the trial. By having more specific criteria for eligible participants, clinical trials are becoming smaller, shorter, more efficient and less expensive.
Big data also allows clinical trials to be monitored in real-time and for any safety or operational risks to be identified, meaning costly delays in the trial can be avoided. Electronic records are used as the main source of data collection for the clinical trial, reducing the chances of manual error and allowing for data to be integrated with real-world evidence. By combining clinical trial information with real-world data such as patient hospital visits, this enables a deeper insight into how the treatment process will play out, which is particularly useful for populations that tend to be excluded from clinical trials such as the elderly or the immobile. Electronic records also mean data is easier to exploit and pass around to be used in the different stages of the pharmaceutical R&D process.
Safety monitoring and detection of adverse reactions
As clinical trials cannot fully replicate real-world conditions, factors such as adverse drug reactions (ADRs) can’t be fully assessed before market launch. The detection of these issues is therefore put into the hands of pharmacists and doctors which can result in information being lost or misinterpreted.
By using big data, analytics in healthcare can incorporate datasets from a wider range of sources. These datasets can be integrated and analysed to detect any ADRs or safety issues with a drug. This includes data from social media, search engines, and online public medical forums where patients commonly report their issues. This data can then be analysed and categorised allowing for not only unreported ADRs to be discovered but also for the detection of any early warning signs of the drug’s health and safety issues. This is a more sophisticated way of monitoring the safety of a drug that allows for faster and more accurate detection of adverse reactions. This provides pharmaceutical companies with a competitive edge when it comes to the regulation processes the drug has to go through while it’s on the market.
Data from advanced technology tools like health-measurement apps in smart devices and mini biosensors can also be analysed to better understand the efficacy of the drug and the adherence of patients to their prescription.
Increased internal and external collaboration
The use of big data has led to pharmaceutical companies becoming less secretive and more collaborative both internally and externally. Internally, data is being shared across different departments not just within the R&D department. The sharing and integration of data allows for more in-depth and analytical insights into the drug development process as well as into the make-up of clinical trials and post-market stages.
Collaboration between external partners such as academic researchers and contract research organisations (CROs) is also proving to be highly beneficial when using big data.
CROs provide more expertise in the process of pharmaceutical R&D and aid in improving the management of clinical trials. Academic researchers also help to provide deeper insights into the most recent scientific discoveries and aid in the innovation of the drug development process.
The future of big data in pharmaceuticals
Due to the increasing use of big data and analytics, the stagnating productivity levels of pharmaceutical R&D is soon to be a thing of the past. The integration of a wide range of data and the use of advanced analytical techniques allows advancements in the R&D process. This is being seen specifically through the ability to effectively predict potential drugs candidates and perform more streamlined and efficient clinical trials.
However, the benefits big data has to offer in pharmaceuticals is not only within the R&D stages. Big data and analytics are also proving to be transforming other areas of the pharmaceutical industry too such as marketing and sales, as well as customer support and regulatory compliance.
The investment in big data within the pharmaceuticals is increasing and with technology becoming more and more advanced, big data is only going to continue to transform the pharmaceutical industry.
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