Spatial computing is revolutionizing life sciences by bridging digital and physical realms, enhancing medical data interaction and patient-specific models. For medtech, it aids in diagnostics and precise interventions, while in biopharma, it accelerates drug discovery through interactive engagements with molecular data. Organizations can pilot augmented reality (AR) and virtual reality (VR) projects in research and development (R&D) and surgical training to grasp the benefits and challenges of these technologies, driving innovation and efficiency across the industry.

Trend in action

In medtech, spatial computing is already revolutionizing how surgeries are performed. Surgeons are using AR goggles to see real-time data overlays during procedures, such as detailed mappings of a patient’s anatomy. This advanced technology is enabling more precise placements of implants or reductions in surgical errors, thereby enhancing patient outcomes.

Similarly, in biopharma, spatial computing is transforming drug discovery. Scientists are engaging with3D models of drug compounds and their interactions with target proteins of interest in real time. This interaction is speeding up the drug discovery process and enhancing the selectivity of compounds, which helps reduce unwanted “off-target” effects that drive adverse events.

Relevance
Biopharma: 3 out of 5
Medtech: 5 out of 5

Readiness
Biopharma: 2.5 out of 5
Medtech: 3 out of 5

GenAI is revolutionizing life sciences by accelerating drug discovery, personalizing patient engagement, and streamlining operations. This technology transforms vast datasets into actionable insights, enhancing efficiency and innovation. GenAI is not just a technological enhancement but a catalyst for growth, making complex processes more agile and tailored, ultimately redefining competitive edges in biopharma and medtech sectors.

Trend in action

GenAI is transforming life sciences by accelerating drug discovery, personalizing patient engagement, and streamlining operations. It predicts protein structures and binding affinities, reducing development costs and increasing clinical trial success rates. GenAI also improves patient outcomes with tailored treatment plans and revolutionizes marketing through hyper-personalized content and precise sales measurements. By integrating GenAI with existing technologies and focusing on key business issues, life sciences companies can enhance efficiency, innovation, and competitiveness in a rapidly evolving industry.

Relevance
Biopharma: 5 out of 5
Medtech: 5 out of 5

Readiness
Biopharma: 3 out of 5
Medtech: 3 out of 5

As the life sciences sector continues to harness the transformative powers of AI and machine learning, a significant trend is emerging: moving beyond brute force compute to smarter, more scalable solutions. This trend is defined by its ability to use advanced computational technologies to enhance efficiency, accelerate innovation, and reduce costs. By leveraging cloud computing’s scalability and AI’s precision, life sciences companies can analyze complex datasets faster than ever, leading to quicker and more effective decision-making processes and outcomes.

Trend in action

An example of this trend can be seen in how major pharmaceutical companies are utilizing cloud-based AI platforms to streamline drug development processes. One notable case is a life sciences company that has implemented an AI-driven platform to predict the success rate of drugs early in the development phase. This use of predictive analytics has allowed the company to make quick decisions about which drug candidates to move forward with, reducing time and expenditure on less promising compounds.

Relevance
Biopharma: 3.5 out of 5
Medtech: 4.5 out of 5

Readiness
Biopharma: 2 out of 5
Medtech: 2.5 out of 5

The pace of innovation is accelerating, necessitating a shift from traditional DevOps to a Developer Experience (DevEx)-oriented approach. DevEx focuses on enriching developers’ environments, fostering technical creativity, and creating a holistic talent ecosystem. This shift can attract and retain top engineering talent, improve efficiency, and enhance product development. By prioritizing a superior developer experience, life sciences companies can unlock productivity gains, reduce time to market, and elevate output quality, contributing to transformative outcomes while fostering a healthier workplace environment.

Trend in action

Life sciences companies are increasingly recognizing the value of improving the developer experience to enhance efficiency and innovation. For example, one multinational pharmaceutical, biotech, and medtech company has begun prioritizing DevEx within its IT strategies, developing robust platforms that can support and engage developers more effectively. These initiatives help improve operational efficiencies and help attract and retain top talent in a competitive market.

Relevance
Biopharma: 4 out of 5
Medtech: 4.5 out of 5

Readiness
Biopharma: 2.5 out of 5
Medtech: 3 out of 5

In an era where digital content can be manipulated with stunning realism, the emergence of synthetic media, such as deepfakes, and disinformation pose unprecedented challenges for many organizations. Synthetic media has the potential to go beyond disrupting individual reputations to undermining public trust and corporate integrity. The life sciences sector, which often relies on the credibility of scientific data and personal health information, stands on the front line of this battle. This trend dives into the critical necessity of defending reality, emphasizing robust digital verification processes to help ensure that authenticity remains uncompromised in scientific communication and data exchange.

A number of tools that help detect synthetic media have already been deployed, such as platforms that train on a petabyte-scale database of text, images, and audio, some of which is artificially generated. These AI models, trained on extensive data, can reliably identify manipulated content. This capability is crucial for enterprises, especially when facing misinformation and disinformation campaigns that could harm the business’s reputation or that of its leadership. Synthetic media detectors are rapidly advancing and will soon become even more finely tuned.

The implications of deepfakes and inaccurate AI-generated content extend beyond misinformation. They represent a direct threat to the foundational trust that underpins patient relationships and scientific discourse. Life sciences companies are now prompted to adopt advanced technologies and strategies to help detect and mitigate these threats. By integrating such measures, companies can protect their own assets and help contribute to the broader integrity of health care and life sciences information across digital platforms.

Trend in action

One leading biopharmaceutical company has implemented advanced digital verification systems for clinical trial data, securing its communication channels against deepfakes. It also integrated blockchain technology with digital asset management systems, leveraging blockchain’s decentralization, immutability, and transparency to ensure data integrity and traceability. This setup can help provide a verifiable and tamperproof record of data provenance, enhancing the credibility of its clinical data.

Relevance
Biopharma: 4 out of 5
Medtech: 5 out of 5

Readiness
Biopharma: 3 out of 5
Medtech: 3 out of 5

Many life sciences companies face pressure from “technical debt”—outdated systems that hinder innovation and efficiency. Addressing this debt is crucial for leveraging modern medicine’s potential. Historically, tech investments met immediate needs but led to disjointed systems, costly to maintain and update. Now, the rapid advancement in genomics, personalized medicine, and patient care technologies necessitates revitalizing IT ecosystems for integrated, agile, and data-driven operations. This shift is strategic, enabling organizations to innovate and improve operational capabilities, as exemplified by a global biopharma company merging old systems into a modern cloud platform.

Trend in action

This trend is illustrated by a global biopharma company that reduced its technical debt by merging several old systems into a single cloud platform. This project not only helped simplify data flows across R&D but also increased regulatory compliance and reduced time to market for new therapies. By moving its data to a modern cloud platform, the company enhanced its operational capability and scalability, allowing it to use real-time data analytics and machine learning for quicker decision-making processes.

Relevance
Biopharma: 4.5 out of 5
Medtech: 4.5 out of 5

Readiness
Biopharma: 3 out of 5
Medtech: 3 out of 5