Life sciences in 2024 is expected to see cautious growth driven by strategic acquisitions and collaborations. While economic headwinds exist, particularly in China, overall M&An activity is predicted to rise, with pharma companies focusing on assets with high commercial potential. Venture capital (VC) funding will likely be selective, favouring companies with strong data and proven track records. Public-private arrangements also offer promising avenues for funding and advancing innovation. 2024 demands strategic agility and collaboration to navigate a dynamic market landscape.

Key takeaways:
 

• VC funding likely to be selective: Venture capital investment in life sciences is expected to stabilise, favouring companies with strong data and proven potential. The IPO market remains tepid.
• Value creation takes centre stage: Companies will prioritise strategies that drive top-line and bottom-line growth through targeted acquisitions and divestitures.
• Collaborations gain traction as alternatives: Biotech companies increasingly turn to partnership models with larger players to access resources, expertise and new Market, especially as funding tightens.

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Generative AI (GenAI) is quickly evolving and affecting life sciences in significant ways. This technology has the potential to revolutionise everything from drug discovery to patient care by automating tasks, improve workflows and optimise processes, leading to significant cost savings and efficiency gains. The vast datasets of life sciences combined with the advanced AI capabilities of tech giants offer powerful synergies for drug discovery and healthcare innovation.

Key takeaways:
 

• String-of-Pearls approach for transformation: Implementing multiple GenAI use cases linked together can transform entire processes across research, development and patient care.
• Personalised patient experiences: GenAI can create personalised experiences for patients, such as AI-powered chatbots for mental health support or customised treatment plans.
• Focus on trust and governance: Addressing concerns about AI bias, explainability and ethical use is crucial for building trust and scaling GenAI adoption.
• Multimodal functionality: LLMs are incorporating text, audio, images and video, enabling more natural human-like interactions and broader applications.

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Global pharma spending is rising, with a shift towards expensive speciality drugs. Governments are implementing price controls to manage costs, raising concerns about reduced R&D investment in the pharmaceutical sector. The US Inflation Reduction Act (IRA) allows Medicare to negotiate drug prices, potentially affecting innovation worldwide. Governments are exploring alternative models to ensure access to essential treatments for all patients, while fostering innovation in truly novel drugs.

Key takeaways:
 

Rising costs and shifting spending patterns: Global pharma spending is accelerating, fuelled by both population growth and a growing demand for expensive speciality medications

Global push for affordability through price controls: Concerns about affordability are leading governments worldwide to implement strict pricing controls on medications.

US price cuts raise innovation fears: The US drug pricing negotiations raise concerns about a potential decline in R&D investment by pharmaceutical companies facing lower profits. While some argue this could stifle innovation, others point out that R&D spending isn't solely tied to the number of new drugs and may even incentivise a focus on truly novel discoveries rather than incremental improvements.

Finding a balance: Affordability, innovation and patient access: Pharmaceutical companies face the challenge of developing strategies to make products commercially viable within pricing constraints. Government should address Issue like the high cost of developing treatments for rare diseases and streamline the lengthy drug approval process.

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Drug development can be viewed as slow and expensive. New technologies like AI are being explored to speed up the process and get treatments to patients faster. This includes better data management, using AI for drug design and collaboration between different organisations. Pharmaceutical companies should look to improve their R&D efficiency to bring treatments to market quicker. How can stakeholders prepare themselves to achieve this?

Key takeaways:
 

• GenAI adoption for speed and efficiency: AI technologies hold promise for faster drug discovery, clinical trials and regulatory approval.
• Data management and talent development: Organising data and building a future-proof workforce are crucial for AI integration.
• Focus on time-to-value: Prioritising speed to market access for life-saving treatments, especially for rare diseases.
• Strategic collaborations: Collaboration between pharma, biotech and research institutions can accelerate R&D progress.

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Life sciences and medtech companies continue to adapt to a shifting global landscape. While traditional globalisation is declining, countries are turning inwards, with China and the US playing key roles. Glocalisation, a mix of globalisation and localisation, is driving changes in trade, manufacturing and R&D. Despite fluctuations in global trade, experts urge monitoring its evolution. Attracting and retaining talent is critical, with promising talent strategies being explored.

Key takeaways:
 

• Declining globalisation, shifting power: Traditional globalisation appears to be waning, with countries adopting policies that prioritise domestic interests. China and the US are major players, with China aiming to become a high-income economy and remain a dominant exporter.
• Glocalisation drives change: Companies are focusing on shorter supply chains, reshoring manufacturing and leveraging government support. This trend, known as glocalisation, is shaping trade patterns and R&D strategies.
• Resilient trade, cautious monitoring: Global trade dipped in 2023 but is projected to rebound in 2024. The World Trade Organisation (WTO) emphasises monitoring recent trends, as some experts remain wary of deglobalisation's impact.
• The talent game: Attraction and retention: Attracting and retaining talent is crucial for R&D innovation. Programmes are incentivising talent return, but established researchers prefer less intervention.

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Healthcare is shifting towards personalised care with a focus on improving patient experiences and outcomes. Shared decision-making (SDM) is a key component, allowing patients to actively participate in treatment choices. However, implementing authentic SDM remains a challenge due to varying patient preferences and provider mindsets. Life sciences companies can play a vital role in promoting SDM by educational resources, patient decision aids (PDAs) and optimising patient touchpoints.

Key takeaways:
 

• Personalised care for improved patient outcomes: Healthcare is prioritising personalised care experiences that go beyond just better treatment options. The goal is to actively involve patients in their care journey, leading to better engagement, adherence and ultimately, improved health outcomes.
• Challenges to authentic SDM implementation: Patients have diverse preferences for involvement, ranging from actively Research options to deferring to a provider's expertise. Some healthcare providers may favour a paternalistic approach, hindering genuine patient participation.
• Understanding the patient journey: A holistic approach: Every disease and patient journey is unique. Healthcare should be adaptable and cater to individual needs and circumstances, whether it's a sudden cancer diagnosis or the gradual progression of a chronic illness.

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