• Sustainability
  • DE&I
  • Pandemic
  • Finance
  • Legal
  • Technology
  • Regulatory
  • Global
  • Pricing
  • Strategy
  • R&D/Clinical Trials
  • Opinion
  • Executive Roundtable
  • Sales & Marketing
  • Executive Profiles
  • Leadership
  • Market Access
  • Patient Engagement
  • Supply Chain
  • Industry Trends

Patients and Data Disrupt the Life Sciences Industry


Delivering better patient outcomes hinges on innovation and adaptability.

Ravinder Singh, Senior Vice President, Consulting, CitiusTech

Ravinder Singh, Senior Vice President, Consulting, CitiusTech

We are at the crossroads of transformative change in the ever-evolving life sciences landscape. The journey ahead promises not only technological advancements and groundbreaking innovations but also a fundamental shift toward patient-centric care.

For instance, the FDA recently announced a 'Patient-Focused Drug Development'1 (PFDD) approach to systematically integrate patients' experiences, perspectives, needs and priorities into the drug development and evaluation process. Why? By leveraging their personal experiences, patients play a unique and invaluable role in enhancing the understanding of the therapeutic context for drug development and evaluation. The insight from this data is invaluable.

Moreover, patients are well-informed and looking for hyper-personalized experiences that are secure, reliable and transparent — factors that have stimulated a widespread change that will outline the future of life sciences for years to come.

Five key areas where patients and data impact life sciences

The new collaboration with patients is generating advanced data insights that is shifting how pharmaceutical, biotechnology, clinical research and medical device research is being conducted. Specifically, it is reshaping the life science industry in five ways.

1. Advanced therapy management

With advanced therapies getting the FDA nod, the prospect for commercialization is looking promising. However, this demands the right tools and technology to aid advanced therapy management progression.

For instance, with gene therapy (GT) applications evolving, manufacturing needs to keep pace. Unlike the initial wave of cell-based GT products, involving local injection and small target populations, the emerging "second wave" of gene-based GT products is characterized by broader indications and systemic delivery. This shift introduces significant variations in production demands, necessitating interoperable and adaptable manufacturing technologies that effectively address supply chain efficacy and safety concerns to meet the diverse needs of this new wave of therapies. Additionally, customizing therapies based on patient endotypes is challenging in advanced therapy management, requiring a nuanced grasp of individual molecular and biological profiles for precise and personalized interventions and optimal treatment outcomes.

Additionally, cloud-based workflows will benefit patients by facilitating multi-appointment scheduling across different care sites and providers, while ensuring compliance with licensing requirements. Cloud solutions will support workflow orchestration, user enrolment, remote care coordination and more, streamlining the management of advanced therapies.

Further, AI is set to play a pivotal role in enhancing advanced therapy management. AI technologies can tailor treatment plans, monitor patients in real-time, predict outcomes, automate diagnostics, support remote care, offer decision support, ensure adherence, integrate data from multiple sources and expedite clinical research.

2. Data-driven decision-making

The continuous digitization of the life sciences industry has significantly increased the volume of medical data. Forecasts suggest that by 2025, global healthcare-related data will reach an estimated 2.5 exabytes2 annually — posing an intriguing scope for data-driven decision-making.

Why do life sciences organizations need to embrace a data-driven mindset? For instance, the FDA reported3 912 drug recalls from 166 manufacturing sites, marking the highest recall count in the past five years. The recalls were attributed to factors like temperature abuse, current good manufacturing practice (CGMP) deviations, inappropriate storage temperatures, manufacturing with a contaminated excipient and more.

With predictive analytics, manufacturers can proactively assess and mitigate these problem areas in real-time based on historical data, thereby preventing public criticism, significant losses for the manufacturers, disruption of supply chains and impediments to the availability of essential medical supplies.

While this is one instance, implementing a data-driven approach is also going to be beneficial:

  • To ensure timely and cost-effective pharmaceutical and medical supply delivery.
  • To optimize the planning and implementation of clinical trials, improving patient recruitment, monitoring and overall trial efficiency.
  • To enable early detection, accurate diagnosis and prediction of disease progression, leading to more effective treatment strategies.
  • To identify potential drug candidates, predict their efficacy and streamline the drug development process.

Real-world data and insights are essential tools for the life sciences industry. This facilitates improved clinical trials, personalized treatments, post-market surveillance, value-based pricing, patient-centric care, data interoperability, AI analytics, regulatory compliance and continuous learning.

3. Integrated medical imaging

With the growing geriatric population and specialization in radiology, the demand for radiologists is on the rise, leading to an increased risk of burnout. The global radiologist shortage is becoming a significant worry, with over 80%4 of health systems acknowledging deficits in their radiology departments.

To address this issue, it’s important to focus on innovating strategies to enhance the efficiency and effectiveness of current radiology teams while taking steps to fill radiological staffing gaps. Integrated medical imaging ecosystems powered by AI can help alleviate the pressure building up on radiologists.

Integrated medical imaging models boost productivity and improve patient outcomes by facilitating the automation and acceleration of routine tasks, extracting patient-centric insights from extensive data sets, and reducing the turnaround time of image reading.

4. Streamlined launch excellence

According to the Journal of the American Medical Association, drug launch prices rose 20%5 annually — from an average of $2,115 to more than $180,000 between 2008 and 2021.

This calls for a significant reform and digitalization of the launch process to facilitate launch excellence. How? By embracing tailored, technology-driven support unique to each client's launch and drawing insights from recent "real-world" launches, organizations can guide cross-functional global launch and PMO teams. In the realm of patient care, pivotal areas for the life science industry's commercial excellence encompass healthcare professional (HCP) & patient segmentation, launch & campaign management and launch enablement.

This approach facilitates shorter project timelines, enhances the quality and precision of plan development, and provides seamless progress visibility at the organizational and leadership levels.

5. Personalized patient engagement

As the underlying theme of this blog suggests, personalization is a critical trend in life sciences, with personalization of patient engagement taking center stage. The democratization of patient information and the growing importance of patient involvement have acted as catalysts for companies to integrate emerging technologies and advanced analytics solutions — necessitating the need to shed a one-size-fits-all model of patient engagement.

Intuitive AI chatbots, telemedicine, virtual clinical trials, data modeling and analysis and personalized medicine will continue to dominate as patients now have access to secure and reliable care in which they are involved in real-time across every stage.

Moreover, with the convergence of omnichannel patient marketing and patient services, the 'retailization' of life sciences is poised to accelerate significantly moving forward.

Accelerating better patient care

In the dynamic landscape of life sciences, where the rules are evolving daily, the year ahead will be characterized by interoperability, personalization and a shift toward patient-centric care steered by technological advancements.

As we delve into how patients and data are reshaping industry, from advanced therapy management to data-driven decision-making, integrated medical imaging, streamlined launch excellence and beyond, it is evident that the future hinges on innovation and adaptability. And the goal is simple: to deliver better and secure patient outcomes.

Ravinder Singh, Senior Vice President, Consulting, CitiusTech


  1. https://www.fda.gov/drugs/development-approval-process-drugs/cder-patient-focused-drug-development
  2. https://www.nature.com/articles/s41437-020-0303-2#:~:text=“Genomical”%20data%20alone%20is%20predicted%20to%20be%20in%20the%20range%20of%202–40%20Exabytes%20by%202025—eclipsing%20the%20amount%20of%20data%20acquired%20by%20all%20other%20technological%20platforms
  3. https://www.fda.gov/media/169611/download
  4. https://www.itnonline.com/article/minding-gap-strategies-address-growing-radiology-shortage
  5. https://www.fiercepharma.com/pharma/runaway-train-drug-launch-prices-have-grown-20-annually-more-decade-and-its-time-congress
Recent Videos
Related Content