Feeling overwhelmed by the hype around AI in life sciences? You're not alone. It's a rapidly evolving field, and it can be tough to know where to start. At Acolad, we're witnessing this transformation firsthand. AI is not only revolutionizing scientific advancements but also reshaping the way critical data, research, and medical knowledge are communicated across languages and global markets.
This report delves into the exciting trends, applications, and ethical considerations of AI in life sciences, based on our recent survey of industry experts from medical device companies (43%), pharma (26%), and those in the clinical trials space (17%).
Whether you're looking to streamline research, improve patient outcomes, or simply stay ahead of the curve, this report will give you the knowledge to help you succeed. Join us as we uncover the challenges and opportunities that lie ahead.
“The future of life sciences is undeniably intertwined with AI. This report serves as a call to action for companies to embrace AI's potential, overcome its challenges, and actively shape an AI-powered future that benefits both the industry and the patients it serves."
Arnaud Daix
Acolad EVP NA, UK and Life Sciences, Linkedin
Key AI in Life Sciences Takeaways
AI Takes the Center Stage
AI continues to shape the future of life sciences, with respondents identifying increased efficiency, cost savings, and competitive advantage as benefits of the technology. Adoption in areas like Marketing (39%) and Diagnostics (22%) highlights its growing impact across the industry.
Prioritizing Ethics
Ethical considerations are at the forefront of AI strategies, with 65% of respondents rating them as very or extremely important. This focus ensures that AI development aligns with industry standards and societal expectations.
The Rise of AI in Language Services
Language services are becoming a key area for AI applications, with 61% already using AI and 70% familiar with its localization capabilities. Transcription (70%) and marketing content creation (48%) emerged as top potential areas for further innovation.
Bright Future, Complex Present
The life sciences industry is embracing AI’s transformative potential, with respondents highlighting future applications such as medical imaging, cancer detection, and enhanced patient communication. Despite this optimism, hurdles like regulatory compliance, data privacy concerns, and integration with legacy systems present challenges that must be addressed to unlock AI’s full potential.
Deep Dive: Life Sciences AI Adoption and Impact
Artificial intelligence is making waves across industries, and the life sciences sector is no exception. A recent survey by Pistoia Alliance revealed that most life sciences experts recognize AI's potential.
Our own survey echoed this sentiment, but it also highlighted that widespread adoption of AI in life sciences is still in its early stages. 78% of respondents indicated they were still exploring AI or had only just begun to implement it within their companies. Companies are focusing on specific areas where AI can deliver immediate value, like marketing and communications (39% adoption rate) and diagnostics (22% adoption rate).
In these specific areas, AI implementation is delivering competitive advantages:
- Marketing & Communication: AI boosts efficiency by crafting materials within regulatory guidelines and enhancing personalization and targeting, helping companies reach a wider and more tailored audience.
- Diagnostics: By analyzing complex data, AI improves diagnostic accuracy and supports early disease detection, such as cancer or heart disease. Personalized medicine and automated diagnostic systems further enhance healthcare delivery.
- Supply Chain Management: AI analyzes historical and market trends to anticipate demand spikes, predict bottlenecks, and draft real-time production plans. It optimizes inventory levels and proactively addresses disruptions, ensuring smoother operations.
- Clinical Trials: From designing studies and drafting protocols to patient recruitment and data analysis, AI is transforming clinical trials. As trials grow larger and more complex, AI accelerates processes, potentially bringing drugs to market faster.
- Pharmacovigilance: AI strengthens pharmacovigilance by detecting safety issues early, expediting adverse event reporting, and supporting informed decision-making for regulatory authorities and pharmaceutical companies.
When asked about the anticipated benefits of AI, respondents highlighted key business advantages:
- Increased Efficiency (78%): By automating routine tasks and streamlining workflows, AI can significantly improve operational efficiency, leading to faster time-to-market for new drugs and therapies.
- Cost Savings (74%): AI can help reduce costs by optimizing resource allocation, improving supply chain management, and streamlining clinical trials.
- Competitive Advantage (74%): Early adoption of AI can give life sciences organizations a significant competitive edge. By leveraging it to innovate and optimize operations, companies can gain market share and strengthen their position in the industry.
This focus on business advantages suggests that while industry professionals recognize AI's potential to address specific challenges within life sciences, they primarily expect broader benefits like increased efficiency and cost savings. However, it's worth noting that respondents also see value in AI's ability to enhance innovation (57%) and improve patient outcomes (61%), demonstrating a growing awareness of its potential to transform patient care and drive medical advancements.
“The McKinsey Global Institute (MGI) has estimated that Generative AI could generate $60 billion to $110 billion a year in economic value for the pharma and medical-product industries, largely because it can boost productivity by accelerating the process of identifying compounds for possible new drugs, speeding their development and approval, and improving the way they are marketed.”
Source: McKinsey & Company report “Generative AI in the pharmaceutical industry: Moving from hype to reality”
Despite the advantages, widespread AI adoption in life sciences remains in its early stages, which explains why the perceived impact of AI on company operations is still relatively moderate. Our survey revealed that only 9% of respondents rated the impact of AI on their operations as a 5, the highest level. Although companies recognize the benefits and potential of AI in life sciences, this slow adoption means that AI’s transformative impact has yet to fully materialize.
AI Challenges & Ethical Considerations
Adopting a transformative technology like AI comes with challenges. Many respondents (61%) are concerned with navigating the complex regulatory landscape. When it comes to regulatory challenges, there are two primary aspects to consider:
- AI-Specific Regulations, such as the EU AI Act that imposes strict requirements on high-risk AI systems, affecting medical devices Class IIa and up.
- Compliance with Patient Safety and Ethical Practices.
Both challenges require companies to stay ahead of evolving regulations which can be time-intensive, implement a comprehensive compliance program, and conduct regular audits. This process takes time and effort but is essential to successfully integrate AI.
Other main challenges identified are data privacy and security concerns, integration with existing systems, and employee training.
- Data privacy and security are particularly critical in life sciences, where sensitive patient information and proprietary research data must be protected from breaches and misuse.
- Integrating AI into existing systems is a complex task. Many life sciences organizations rely on legacy infrastructure that may not be compatible with modern AI solutions. Ensuring high-quality, accessible data is also crucial for effective AI implementation.
- Employee training also presents another significant barrier. As AI technologies evolve rapidly, professionals often require new skills and knowledge to work effectively alongside AI systems. This requires substantial investment in upskilling and reskilling employees, which can be time-consuming and costly, especially in a field where precision and expertise are paramount.
When it comes to ethical considerations, the survey reflected the industry's commitment to responsible innovation, with 65% saying that they prioritize ethics in AI strategies (very important and extremely important). This reflects a growing awareness of the need to align AI technologies with ethical principles, particularly regarding data privacy, bias, and the societal implications of AI applications.
As AI continues to advance, striking a balance between innovation and ethical considerations is essential. By prioritizing ethical principles, life sciences organizations can build trust with patients, regulators, and the public. This can be achieved through developing ethical guidelines, investing in AI ethics training, and implementing robust monitoring and auditing of AI systems.
“When assessing AI use in life sciences, we're not just dealing with data and algorithms; we're dealing with human lives and wellbeing. Ethical considerations are not merely a checkbox but a guiding compass, ensuring that AI is used responsibly to improve patient care and uphold the values we hold dear."
Manchandan Sandhu
Acolad Life Sciences General Manager, Linkedin
The Growing Buzz Around AI in Language Services
The life sciences industry is increasingly recognizing how AI can revolutionize language services, and our survey results confirm this trend. A whopping 70% of respondents are familiar with AI applications for translation and localization, and 61% of companies have already integrated AI into their language-related tasks, such as translation, interpreting, and content creation. This shows that AI is quickly becoming a go-to tool for streamlining language services in life sciences.
AI-driven solutions like machine translation (MT) and large language models (LLMs) offer a range of benefits. They can accelerate content creation and distribution, helping companies meet tight regulatory deadlines and ensuring that vital information reaches authorities and stakeholders quickly. This can be a game-changer, speeding up the time-to-market for new products and therapies.
But it's not just about speed. AI can also enhance accuracy and efficiency in various language-related tasks:
- Transcription of Audio and Video Content (70%): AI-powered tools can transcribe clinical trials appointments, interviews, and other audio and video content, freeing up valuable time and resources.
- Marketing Content Creation and Translation (48%): AI can help life sciences companies reach a global audience by generating high-quality marketing content in multiple languages.
- Multilingual Patient Engagement and Support (39%): AI-powered chatbots and virtual assistants can provide support in multiple languages, improving patient satisfaction and helping them stick to treatment plans.
- Pharmacovigilance Reporting Translation (17%): AI can streamline the translation of adverse event reports, enabling faster identification and response to safety signals.
Finding the Right Balance: Human Expertise and AI
While AI offers huge potential, it's important to remember that relying solely on AI for language services comes with challenges. AI models need high-quality data to produce accurate translations, and they may struggle with the nuances of complex scientific language, cultural context, and ethical considerations.
Our survey found that 43% of respondents believe that an ideal scenario involves 26-50% AI involvement in language services. This highlights the importance of human oversight and intervention. A hybrid approach, combining the strengths of human linguists with AI tools, can lead to the best results.
One such approach is machine translation post-editing (MTPE), which uses machine translation, or AI for the initial translation and then has human experts review and refine the output. This ensures both speed and accuracy, delivering high-quality translations.
As the 2024 Slator report highlights, MTPE is gaining traction in the life sciences industry, proving its value in navigating time-sensitive scenarios and ensuring accurate communication. For instance, during clinical trial submissions, where tight regulatory timelines can be challenging, MTPE can help expedite the translation of requests for information from health authorities. Similarly, in pharmacovigilance, where rapid reporting of adverse events is crucial, MTPE can ensure timely and accurate communication with regulatory agencies.
We can now go several steps further to reduce the scope of human involvement by carefully tested automated post editing (APE) and automated quality estimation (APE), all the while balancing risk management and efficiency.
The Promise of AI in Life Sciences
While the potential of AI in the life sciences industry is widely recognized, individual perspectives on the technology vary. Our survey revealed a range of sentiments among industry professionals:
- The Optimists (52%): This group views AI as a transformative technology with the power to enhance efficiency and innovation, streamline processes, accelerate research, and ultimately improve patient outcomes.
- The Pragmatists (35%): This group sees AI as a valuable tool that can simplify tasks and improve productivity when applied correctly.
- The Cautious (13%): This smaller group expressed concerns about the complexities and challenges associated with AI, particularly regarding regulatory compliance.
These diverse perspectives highlight the multifaceted nature of AI in life sciences. While it holds immense potential, it also presents challenges that require careful navigation to ensure successful implementation and meaningful benefits.
Regardless of their individual perspectives, respondents expressed excitement about the future applications of AI in the life sciences industry. They identified a range of potential benefits, including:
- Medical Image Processing: AI can analyze medical images quickly and accurately, revolutionizing diagnostics and enabling earlier disease detection and more precise interpretations, especially in fields like radiology, pathology, and oncology.
- Individual Diagnostics and Personalized Therapies: AI has the potential to personalize healthcare by tailoring treatments to individual patients based on their unique genetic, clinical, and lifestyle data, ultimately enhancing treatment efficacy and patient outcomes.
- Cancer Detection and Predictive Analytics: AI can analyze vast datasets to identify patterns, leading to significant strides in early cancer detection, risk prediction, and the development of targeted therapies.
- Real-World Data Analysis: AI can process and analyze real-world evidence, improving clinical decision-making, understanding patient populations, and identifying trends that drive innovation.
- Patient Communications and Engagement: AI-powered tools can enhance communication between life sciences companies and patients, providing better education, support, and overall communication throughout the care journey.
These potential applications highlight the diverse ways in which AI can transform the life sciences industry. There's a strong sense of optimism about the future of AI in this field, and as AI continues to evolve, we can expect even more innovative applications that will revolutionize healthcare and improve patient outcomes.
“Looking ahead, AI promises to revolutionize not only what we achieve in life sciences, but how we achieve it. This report highlights the exciting possibilities that lie ahead, where AI-powered advancements can revolutionize diagnostics, personalize treatments, and accelerate medical breakthroughs, ultimately transforming the way we prevent, detect, and treat diseases.”
Manchandan Sandhu, Acolad Life Sciences General Manager
