Organizations have increased tech adoption over the past two years, however, life science analytics trends 2023 are crucial to maintaining the progress of everything from supply chains to clinical trials. As the health crisis’ initial phase passed, organizations realized they had made progress in several crucial areas: patient confidence rose, decentralized clinical trials demonstrated their validity, and virtual tools highlighted the advantages of having a diverse, global conversation throughout the product development process.
Life sciences organizations will typically look hard for efficiency, especially in highly regulated activities. These opportunities will be found in the standardization and modernization of insight-gathering procedures, the adoption of novel strategies for particular problems, and the use of technology designed specifically for drug and device development, from early-stage research and development to post-market surveillance. We’ve listed below key five trends that will impact the life sciences industry.
Insights Management
Life science teams are becoming aware that insights management is among the most crucial business processes and needs the same level of rigor and technology support as other crucial business processes. Organizations will consider insights management as an essential pillar in turning insights into actions easily.
The proper insights management platform will be just as important as the right CRM given that life science teams move away from the slow and fragmented methodologies of the past to close the insight gap. Industry leaders are discussing how their work has changed and how they are prepared for a new strategy aligned with pharma analytics.
Next-gen real-world evidence
With real-world data (RWD), Life sciences companies can learn more about how their treatments are used. The industry can only assist regulatory choices, such as approving new indications or label expansions for existing medications and accelerating clinical trials by unlocking value from RWD. Leading life sciences and healthcare firms leverage data to support observational research to improve treatment methods and clinical trial designs.
Pharma companies would need to adopt a practical and cooperative approach with end-to-end (E2E) evidence management strategies, dismantling traditional evidence silos with platforms and procedures to make data and knowledge assets easily accessible throughout the organization and drive data-driven decision-making. However, developing and putting into action such plans will probably call for an evaluation and realignment of their existing infrastructure, governance, operating models, people, and processes.
RWD, as opposed to clinical trials, is observational data that is often acquired when a medical product is on the market and being used by “real” people in real life. The US Food and Drug Administration (FDA) lists a number of potential RWD sources, including electronic health records, claims, illness, and product registries, patient-generated data, and information acquired from additional sources that can provide details about a patient’s health.
Cut through the chaos
If insights are valuable, many businesses struggle, and it’s not for lack of knowledge. However, facts, figures, and observations are not insights, which are crucial ideas that have an impact on smart decision-making. The decisions made by life science teams may be based on information that is out-of-date or incomplete if critical insights are lost in the shuffle of paperwork, emails, meeting notes, and transcripts.
Smart automation
The internet of things (IoT), blockchain technology, augmented reality (AR), virtual reality (VR), machine learning (ML), robotic process automation (RPA), artificial intelligence (AI), and the ever-increasing use of data analytics in pharmaceuticals have transformed the game. Numerous jobs in the life sciences industry now have higher levels of productivity, precision, and compliance – thanks to modern digital platforms and software.
Approximately 83% of the industry respondents polled, according to ArisGlobal’s Market Research Report 2021, their organizations apply automation across their R&D processes, whether it be by automating particular activities using rule-based automation or by implementing more cutting-edge technology. Cost efficiency, improved quality compliance, and streamlined operations are some of the main advantages of leveraging automation technologies.
Additionally, the respondents hope to improve decision-making, expedite cross-functional cooperation, and boost flexibility and scalability by gaining deeper insights. In the subsequent years, it is likely to be seen that intelligent automation will become more prevalent, particularly in sectors like manufacturing, quality, and commercialization.
What are the new supply chain management innovations in pharmaceutical industry?
In order to improve their systems, processes, and data management, life sciences organizations are laying great focus on the most recent medical supply-chain management techniques. This is the initial phase of improving the value stream’s delivery and cost performance, and it entails the adoption of new planning and aggregation techniques, new inventory management procedures, and enhanced demand-to-capacity and workload translation techniques.
By implementing industry-proven practices and leveraging pharma analytics, organizations can streamline operational performance, maximize productivity, and boost efficiency. Predictive analytics, enhanced supplier communication, e-payables, and cloud computing are the key trends in supply chain management. Supply-chain management has been more productive – thanks to the growing usage of digitization, AI, and automation, which has strengthened the process overall and made it more effective.
To conclude, the above-mentioned trends will impact the life sciences industry, and now may be the ideal time to discover the right ways of working and the use of the right technology processes for your work. Get in Touch with Polestar Solutions to discover how we help forward-thinking life sciences organizations leverage new trends and technologies to spur transformation and boost organizational growth.