Exploring Digital Transformations in Life Sciences, Biomedical Affairs

October 30, 2023 - The life sciences and biomedical sector is undergoing a profound transformation driven by digital technology. In recent years, integrating digital tools, data analytics, and artificial intelligence (AI) has ushered in a new era of efficiency, innovation, and patient-centered care. These digital transformations shape the future of healthcare and present many opportunities and challenges for stakeholders in the industry.

Accelerated Drug Discovery

Digital technology has significantly accelerated drug discovery, a complex and costly endeavor in the pharmaceutical industry. With advanced computational models and AI algorithms, researchers can now analyze vast datasets and simulate drug interactions.

A prominent example is Atomwise, known for its AI-driven drug discovery platform, which has transitioned into a pharmaceutical company with the nomination of its first AI-driven candidate, a TYK2 inhibitor. Atomwise aims to differentiate itself by exploring unique chemical space and building an internal drug pipeline while focusing on various therapeutic areas, including inflammatory diseases, oncology, and immunology. This technology expedites the drug discovery process and makes it more cost-effective, potentially bringing life-saving medications to market more quickly.

Precision Medicine

Precision medicine, which tailors treatments to the genetic makeup and unique characteristics of individual patients, has been made possible through digital transformations. Genomic sequencing and advanced data analytics enable healthcare providers to create personalized treatment plans.

In the United States, the All of Us Research Program, led by the National Institutes of Health (NIH), exemplifies the power of digital transformations in advancing precision medicine. This large-scale initiative collects genetic and health data from over one million diverse participants to gain insights into individualized healthcare, enhancing treatment precision and effectiveness by tailoring medical interventions to patients' unique genetic and health profiles.

Remote Patient Monitoring

Telemedicine and remote patient monitoring are becoming increasingly prevalent, offering patients more convenient access to healthcare while reducing the burden on the healthcare system. Devices such as wearable fitness trackers, blood pressure monitors, and glucose meters provide real-time data that healthcare professionals can remotely monitor.

One noteworthy tool in the fight against diabetes is the integration of continuous glucose monitoring (CGM) devices, such as Abbott Freestyle Libre 2 and 3, Dexcom G6 and G7, Medtronic Guardian Connect and Guardian Sensor 3, and Senseonics’ implantable Eversense.

"CGMs tailor care to the individual, helping patients fine-tune their diabetes management based on their specific needs,” said Tina Platania, PharmD, Director of Clinical Services at CCS and a certified diabetes care and education specialist, in an episode of Healthcare Strategies.

“The immediate feedback provided by CGMs helps patients and healthcare providers identify patterns and make adjustments to medication, diet, and lifestyle choices — it's a great benefit,” she added.

Electronic Health Records (EHRs)

Electronic health records (EHRs) have transformed how patient information is stored, accessed, and shared. EHRs have improved the accuracy and accessibility of patient data, leading to more informed decision-making.

Epic Systems, a prominent EHR solutions provider, plays a pivotal role in linking healthcare institutions and optimizing the exchange of patient data, with over 305 million patients having up-to-date electronic records on their platform. This digital evolution mitigates mistakes, improves the coordination of patient care, and encourages individuals to become more engaged in managing their healthcare.

AI in Diagnostics

AI has the potential to revolutionize diagnostics, improving accuracy and speed. Deep learning algorithms can analyze medical images, such as X-rays and MRIs, to detect anomalies and assist in diagnosing diseases.

PathAI, for instance, uses AI to assist pathologists in diagnosing diseases from tissue samples. This technology improves diagnostic accuracy and frees valuable time for healthcare professionals to focus on more complex cases.

In March 2023, PathAI introduced AISight, its digital pathology platform, and the AIM-PD-L1 NSCLC RUO algorithm in collaboration with 13 prominent healthcare institutions across the US, to advance precision medicine through the application of digital pathology tools, including AI-powered algorithms for the quantification of PD-L1 positive tumor and immune cells in non-small cell lung cancer samples, to enhance patient care and research. These leading laboratories will pioneer the adoption of digital pathology, leveraging PathAI's technology, user-friendly interface, and a suite of immunohistochemistry quantitation algorithms for various cancer indications, building upon PathAI's previously validated AI-powered PD-L1 algorithms.

Predictive Analytics for Outcomes

Predictive analytics powered by digital technologies enable healthcare organizations to anticipate patient outcomes and allocate resources more effectively. For instance, the Cleveland Clinic uses predictive analytics to identify patients at high risk of readmission, allowing for timely interventions and reducing healthcare costs. Healthcare providers can make more informed decisions and improve patient care by analyzing historical data and monitoring patient progress in real-time.

Drug Repurposing

Digital transformations have also paved the way for drug repurposing, identifying new therapeutic uses for existing drugs. Companies like BenevolentAI are at the forefront of this field, using AI and data analysis to explore new applications for existing medications. This not only accelerates the development of new treatments but also has the potential to lower drug development costs.

In April 2022, BenevolentAI and the Drugs for Neglected Disease initiative (DNDi) initiated an AI research project to address dengue, a significant global infectious disease with no effective treatment, using AI to identify potential biological targets and repurposed therapies to prevent disease progression, aiming to deliver promising drug candidates for clinical trials. Dengue — a climate-sensitive and neglected disease — affects millions worldwide, and this collaboration leverages AI technology to accelerate research efforts and provide potential solutions to this urgent public health challenge.

Real-World Evidence

Real-world evidence (RWE) gathered from patient experiences in everyday clinical practice is becoming increasingly valuable for decision-making in healthcare. The FDA has recognized the importance of real-world evidence and is actively working to incorporate it into regulatory decision-making.

For example, the US Food and Drug Administration (FDA) has initiated the Advancing Real-World Evidence Program, which focuses on improving RWE-based approaches for new medical product labeling claims, post-approval study requirements, and supporting regulatory decision-making. This program provides a pathway for sponsors to discuss the use of RWE in medical product development with the FDA, offering the opportunity to disclose RWE use cases while ensuring data integrity and relevance.

Challenges and Considerations

While digital transformations offer numerous benefits, they also present challenges and considerations for the life sciences and biomedical sectors.

Data Privacy and Security

The collection and sharing of sensitive patient data raise concerns about privacy and security. As healthcare organizations store and exchange large volumes of patient information, robust data protection measures are crucial to prevent breaches and ensure patient trust.

Regulatory Compliance

The use of digital technologies in healthcare is subject to strict regulatory oversight. Navigating the complex landscape of regulations and ensuring compliance with standards like HIPAA in the US and GDPR in Europe is an ongoing challenge for healthcare organizations.

Integration and Interoperability

To reach their full potential, digital healthcare systems must seamlessly integrate with existing healthcare infrastructure and systems. Achieving interoperability is essential to ensure data can be shared among providers and platforms.

Access and Equity

While digital healthcare holds great promise, it raises concerns about access and equity. Not all patients have equal access to digital healthcare solutions, potentially exacerbating health disparities. Efforts are needed to ensure that these innovations benefit all population segments.

The life sciences and biomedical industry must continue to adapt to the rapidly changing digital landscape, harnessing the power of data and AI to drive progress and ultimately redefine the future of healthcare. In an era where data is the new currency, integrating digital technology in healthcare is not just an option; it's necessary to meet the growing demands and challenges of the 21st century.