Chris Llewellyn

⏩️ excellent review! maybe we need to reneame it “from raw data to evidence (#RWE)” in our ecosystem? 🔂 maybe we need to revisit the value of such data for public health in light of financial implications described in other settings? 🆓 nothing is for free but maybe better utilizing the abundance of already available data could dramatically reduce costs - rendering healthcare delivery as well as R&D much more efficient! 🔀 Full disclosure: no affiliation!

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Digital Health Unplugged Podcast: Why is the NHS so difficult to sell to? https://lnkd.in/emEnAtY6 Jordan Sollof, reporter at Digital Health News, is joined by Lloyd Price and Mohammad Al-Ubaydli to talk about procurement and why the NHS is so difficult to sell to. From their own experience, Price, a HealthTech founder, M&A advisor for Nelson Advisors and Non-Executive Director for various Digital Health companies, and Al-Ubaydli, Founder and Chief Executive of Digital Health social enterprise, Patients Know Best, shine a light on the main issues that can make selling to the NHS a challenge. The pair discuss success stories of startups which have successfully sold to the NHS, before assessing whether companies and suppliers need to take more care in ensuring they are pitching the right solution to the right organisation. They give their views on whether the NHS procurement process has become overcomplicated, a point raised in a session at Rewired 2024, and speculate whether the forthcoming Procurement Act (which was originally due to come into force in October 2024, but has been delayed until February 2025) will solve some issues and make it easier for those selling in the health technology sector. Finally, the guests predict what they anticipate will happen in the coming months and years, including whether the NHS will become a simpler system as a whole to sell to or if we will still be having the same conversation about difficulties selling in a few years’ time https://lnkd.in/emEnAtY6

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The power of AI in healthcare continues to improve health outcomes and access to care, significantly improving prognosis and survivial rates.

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The UK's delicate industrial strategy balancing act: our service industry must embrace GenAI, but the risk is that we hand our future to US BigTech. My article in Bright Blue's new collection of essays on the impact of Generative AI, alongside such luminaries as Kenneth Cukier Rose Luckin Gerard Grech Tom Watson. "It is easy to be cynical about endless promises surrounding the transformative potential of AI. However, even if the current break-neck pace of technological development were to slow down, we are already seeing the first stirrings of a productivity revolution, especially in the services industry. This matters because the UK is the second-biggest exporter of services in the world, and, at present, we face a conundrum. If we do not embrace the AI opportunity, then we risk falling behind and losing our competitive edge. But, if we do fully embrace AI, we risk handing the keys to our economy over to the US tech giants on whose AI platforms our technological future depends." Let's hope that the next Government has the bandwidth and vision to focus on both aspects of this challenge. Do check out pages 38-39 (as well as all the other great articles obviously) for the Best Practice AI view on this. With thanks to Sarah Kuszynski and Ryan Shorthouse. https://lnkd.in/g8CJtAkJ

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Really stimulating start to the day on a panel about ‘dark data’ (the untapped data in healthcare) at the Digital Healthcare Show. It was chaired by the brilliant Anushka Patchava MD, MBA. Some key takeaways - As we’re all consumers of healthcare do we have a responsibility to share our own data to ensure better outcomes for not only ourselves, but others ? - If we want to unlock the power of data then we need clinicians engaged, involved and empowered. - There’s huge promise in using data that we don’t currently collect, especially when it comes to logistics and operations. There’s the potential to look at ‘low hanging fruit’ to maximize efficiency and impact. Special thanks to my fellow panelists Ian Gargan, Dr Cos Fantis and Kassim Hussein Hussein as well as Anushka Patchava MD, MBA for asking me to be part of the panel. #data #healthcare #digitalhealthcareshow

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https://lnkd.in/dAJMeYx3 Our portfolio company Seegnal initiates business in the UK. Seegnal is a smart and intuitive clinical decision support platform that empowers clinicians to quickly & effectively manage and resolve patient-specific Drug Related Problems (DRPs). Seegnal’s unique approach shows a reduction of up to 94% in Alert load, while achieving a 98% alert accuracy as a result of its patient-tailored alert algorithms and single screen graphic interface. Seegnals interfaces with the Electronic Medical Record (EMR) or any other relevant platform and incorporates the widest scope of relevant patient data into an intuitive, all-in-one, patented interface. Eyal Schneid Dr. Shiri Guy Alfandary, PharmD. Jack Steckel Oded Orgil 🎗️

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The Economist highlights productivity as a pressing problem within the UK National Health Service, just as it is the case in other countries. I'm proud that the AI-backed data platform of DEO.care, succeeds time and time again to increase surgery volume in #hospitals and #ASC's in both Europe and the US while at the same time reducing the fatigue of the surgical teams involved. That way we can help keeping #healthcare viable. #medtech #digitaltwin

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With a commitment to “Health for All and All for Health,” we must not delay life-saving health technologies. Global health authorities and legislators should collaborate to develop a streamlined pathway for the approval and certification of these critical innovations, ensuring faster access to those who need them most.

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My new report with FemHealth Insights on #DigitalHealth is out! A $2.5b sector within #WomensHealth that had a ton of data to dive into. Available for purchase on femhealthinsights.com.

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A short and useful read on this crucial topic.

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Medical Record Automation: MRA emerges as one of the key HealthTech sub sectors in 2024 https://lnkd.in/e4GKYsxW Medical Record Automation is the process of using technology to streamline and optimise the management of patient health information. It involves the digitalisation, storage, retrieval, and analysis of medical records to improve efficiency, accuracy, and accessibility. Medical Record Automation (MRA) has undeniably emerged as a critical subsector within HealthTech in 2024. It's driven by a perfect storm of factors: Increasing data volumes: The sheer amount of patient data generated daily is overwhelming. Demand for efficiency: Healthcare providers are under immense pressure to reduce costs and improve patient care. Data privacy concerns: Securely handling sensitive patient information is paramount Nelson Advisors work with Healthcare Technology Founders, Owners and Investors to assess whether they should 'Build, Buy, Partner or Sell' to maximise shareholder value.   HealthTech Mergers, Acquisitions, Growth & Strategy > www.nelsonadvisors.co.uk   Nelson Advisors HealthTech M&A Newsletter > Subscribe Today! https://lnkd.in/e5hTp_xb   Buy Side, Sell Side, Go To Market, Partnership Strategies > Email [email protected]   Nelson Advisors HealthTech Thought Leadership > Visit https://lnkd.in/ezyUh5i   #HealthTech #DigitalHealth #HealthIT #NelsonAdvisors #Mergers #Acquisitions #Growth #Strategy #Partnerships #VentureCapital #PrivateEquity https://lnkd.in/e4GKYsxW

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Interesting read on how #AI is revolutionising the pharmaceutical industry i) Drug Discovery - AI is accelerating the identification of new drug candidates and optimising trial design ii) Boosting success rates in Phase 2 clinical trials (assessing efficacy and safety) iii) Cutting costs and improving ROI Check out this insightful article where Remco Jan Geukes Foppen looks into the impact of AI technologies like #ML and #GenAI on target discovery and post-approval monitoring in the industry. https://lnkd.in/e9AW-GNi #Pharma #ArtificialIntelligence #DrugDevelopment

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Thank you for sharing this insightful research, Dario Heymann, PhD. The increasing role of Big Tech in Digital Health is undeniable and, as your analysis highlights, their resources and technological capabilities are instrumental in driving innovation forward. The impressive growth rate of partnerships, particularly with a CAGR of 32%, underscores the strategic importance of these collaborations. In my experience, the synergy between Big Tech and Digital Health startups fosters a dynamic environment where advanced technologies like AI, machine learning, and blockchain can be seamlessly integrated into healthcare solutions. This not only enhances healthcare delivery but also aligns with patient-centric values and stringent regulatory requirements. Moreover, the shift of Big Tech overtaking Biopharma in partnership share is a clear indicator of the evolving landscape. It’s essential for startups, academic institutions, and healthcare organizations to leverage these partnerships to stay at the forefront of innovation. #eHealth #HealthTech #DigitalHealth

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One of the hugely positive impacts that AI is expected to have on society in the coming years, is in the healthcare sector. And that is why I was delighted to attend the official opening of the SAS Advanced Analytics Hub at The Maxwell Centre, University of Cambridge last week. The partnership aims to accelerate healthcare innovation through enhanced access to advanced analytics. It will embed SAS experts and SAS® Viya® data and AI platform capabilities into the University environment, enabling targeted collaboration to “find the quickest way from a billion points of data to a point of view”. The hub will have capacity to recruit and support several high-quality, high-impact academic research projects and promising early-stage startups in the health-tech space, providing their innovative ideas with extra momentum. We believe this combination of expertise can tackle some of the world’s biggest challenges, which is why it’s such an exciting project. We’ve already had a taste of what can be achieved. A University of Cambridge-led project on kidney transplants, PITHIA, developed an AI-based decision support approach using SAS’ analytics platform. It is being used to automate the process of scoring biopsies for kidneys to better identify those organs that can be used for transplantation. This has the potential to save lives and transform the quality of life for more than 100 people each year who would otherwise require dialysis, as well as saving the NHS millions of pounds annually. Professor Nigel Peake (Chair of the Maxwell Centre) and Gail Stephens (Vice President Health and Life Sciences at SAS) formally opened the analytics hub and it was a great pleasure to be joined by distinguished individuals involved in scientific research, as well as SAS colleagues. And a massive thank you to those that made this partnership possible, including Dr Alexander Samoshkin, from the Office for Translational Research at the University, and Dr Agnieszka Iwasiewicz-Wabnig FRSA, Maxwell Centre Director. I would like to thank all those involved in the organisation of the event including Monica Lucena, Katy Cordingley, Mayra Pedraza, Anne Okwuzi and special thanks to the SAS team who worked so hard to secure this collaboration: Geoffrey Taylor, Glyn Townsend, Mark Lambrecht, Stephen Kearney, Anu Sharma Pereira, David Shannon, Peter Andersen and Nicky Furlong. #CambridgeUniversity #Partnership #DataForGood #Analytics #AI #healthcare

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The University of Cambridge and SAS have announced a strategic partnership aimed at accelerating #healthcare innovation through advanced analytics. This collaboration has already demonstrated its potential by addressing critical healthcare challenges. The #PITHIA project, led by Professor Gavin Pettigrew, utilised SAS’s dynamic analytics platform to develop an AI-based decision support system for kidney transplants. This innovative approach automates the process of scoring kidney biopsies, enhancing the identification of viable organs and thereby increasing the number and success rate of transplants. Dr. Alex Samoshkin, Deputy Head of the Office for Translational Research at the School of Clinical Medicine, initiated this partnership. He noted that in 2018, he supported the PITHIA project, and SAS proved to be the ideal industrial partner. The collaboration demonstrated that the synergy between the University and SAS was crucial in accelerating the transition from innovative ideas to clinical application. Building on this success, the partnership is set to expand. In June 2023, the Cambridge team visited SAS headquarters in Cary, NC, USA, to discuss further collaboration opportunities with senior SAS leadership, including co-founder and CEO Dr. Jim Goodnight. This partnership exemplifies the impactful convergence of academic research and industrial expertise, promising significant advancements in healthcare technology. #HealthcareInnovation #AI #Analytics #UniversityOfCambridge #SAS #MedicalResearch #KidneyTransplant #HealthcareTechnology

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Day 1 of UKIO 2024 has been a buzz 🐝 Qure.ai Taking in thoughtful talks (tackling acute imaging workload with AI, the pathway to enable auto-reporting by AI), seeing collaborators off a screen, having individual discussions with first time AI users or lessons learned from existing AI implementations - have all made for an exciting first UKIO for me. If you’re still reading 🤓, here are 5 operational takeaways that resonated with me (in no specific order): 1. On human-AI interaction: if AI can detect normal chest x-rays with high accuracy, and might eventually take that workload on, how do we ensure future trainees are still well versed in reading normal scans? From an RSNA discussion (source pending): maybe 5% of scans are randomly unprocessed by AI to keep human readers up-skilled? 2. Lots of talk about performance standards that AI is held it up to, but what standards are human readers held to? Is this the threshold for AI success? 3. About to start your AI deployment journey? Having your success metrics planned, and importantly the methods for collecting these metrics (coding your reports as ONE example) - will make AI monitoring breezier. More nuanced conversation than this of course. 4. More of a point 3b, monitoring AI and reader disagreement in either direction, without disrupting clinical workflows is essential to adoption and safety. Are platforms the answer? Natural language processing? TBD. 5. Despite the best of of technology, AI and digital solutions on display at the conference - at the end of the day this is about people, patients, radiologists, researchers, engineers… so I’m very grateful to be surrounded by people just as passionate about medical imaging Surabhi Srivastava Georgina Wright Andy Murray Ben Tromans Viswas Kumar Maddila Irina Wade Vatsal Khetan UKIO

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We have just released our latest Insight Brief on Advancing Digital Health Innovation using Real World Evidence! Check it out below. Thanks for sharing Brian Lovinguth!

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How should HealthTech companies approach clinical evidence generation? Dr Saira Ghafur from Prova Health delivered an amazing masterclass yesterday on this very topic. 👇 𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐤𝐞𝐲 𝐩𝐨𝐢𝐧𝐭𝐬: 1. 𝐁𝐞 𝐜𝐥𝐞𝐚𝐫 𝐨𝐧 𝐭𝐡𝐞 𝐩𝐮𝐫𝐩𝐨𝐬𝐞 𝐨𝐟 𝐲𝐨𝐮𝐫 𝐞𝐯𝐢𝐝𝐞𝐧𝐜𝐞 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧. Three key questions founders should ask is: - Who am I generating this evidence for? (Investors, NHS, Clinicians, Procurement) - What stage of product development are we in? (Early product development, Regulatory approval, Reimbursement) - What key endpoints do I have to demonstrate? (Clinical safety, efficacy, value for money, reliability) Depending on your answer, your choice of study design would vary wildly. 2. 𝐄𝐜𝐨𝐧𝐨𝐦𝐢𝐜 𝐞𝐯𝐢𝐝𝐞𝐧𝐜𝐞 𝐢𝐬 𝐠𝐫𝐨𝐰𝐢𝐧𝐠 𝐢𝐧 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐜𝐞. Clinical evidence is table stakes. (Without which, the conversation cannot even start.) But there is now a major shift towards the economic evidence of any product. - Is it cost effective? - Can it reduce expenses? - Is it cash releasing or cost saving? - Does it reduce healthcare utilisation? Economic evidence is increasingly popular amongst payors and investors, so it will be prudent to plan for this too. 3. 𝐓𝐡𝐞 𝐛𝐚𝐫𝐫𝐢𝐞𝐫𝐬 𝐟𝐨𝐫 𝐜𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐞𝐯𝐢𝐝𝐞𝐧𝐜𝐞 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐜𝐚𝐧 𝐛𝐞 𝐨𝐯𝐞𝐫𝐜𝐨𝐦𝐞. 2 of the biggest challenge to generating evidence are: - Finding a suitable/willing clinical site. - Securing funding needed for this. 🤝 Finding a clinical site is a matter of relationship building. Any clinical study comes with its own risk. Be it reputational, risk to patient or risk of time wasted. Companies should invest time and effort to build trust with clinicians and site managers - approaching them via NHS accelerators and health innovation networks can help build credibility too. Lastly, founders should keep an eye out for the various grants available out there - as there are quite a few that does support evidence generation in the early stages! _____________________________________________ All in all, a great talk with a good turnout! Thank you Saira for taking the time! Do check out the recording if you want to learn more! (Links in comments) Gianluca Fontana | Ben Porter | Dr. Sam McInerney | David Lowe | Nina Sesto, PhD | Simba Mavhunga | Jacob Mathew, MD | Guy Parsons |

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