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Shareholder agreements for healthtech startups often include preferred shares, which have rights that are superior to common shares. Within preferred shares, the most critical distinction for founders to understand is between participatingand non-participating preferences, as this directly impacts how much money investors receive during a liquidity event (like an acquisition or IPO) and consequently, how much is left for the founders and common shareholders.Non-Participating Preferred Stock 🤝This is the most common and founder-friendly type of preferred stock.How it Works: When a company is sold, non-participating preferred shareholders have a choice:Get their money back: They can take their initial investment back, plus any accrued dividends. Convert to common stock: They can convert their preferred shares into common shares and get their proportional share of the sale proceeds, just like everyone else. Payout Logic: They will choose whichever option gives them a higher return. For example, if an investor put in $10 million for 20% of the company and the company sells for $100 million, they will get $20 million by converting to common stock (20% of $100 million), not just their initial $10 million back. The Founder's Takeaway: This model means investors get a return or a proportional share of the equity, but not both. This leaves more value for founders and common shareholders, especially in a high-value exit. Participating Preferred Stock 💰This type of preferred stock is less common for early-stage companies and is generally more investor-friendly.How it Works: Participating preferred shareholders get their initial investment back first, and then they get to participate in the remaining sale proceeds along with the common shareholders, based on their ownership percentage.Payout Logic: The investor's payout is a two-step process:Liquidation Preference: The investor gets their initial investment back off the top. Participation: After the initial investment is returned, the remaining money is distributed as if the preferred shares had converted to common stock. The investor gets their proportional share of this remaining pot.Example: An investor puts in $10 million for 20% of the company, and the company sells for $100 million.Liquidation Preference: The investor gets their $10 million back. This leaves $90 million for distribution.Participation: The investor then gets their 20% of the remaining $90 million, which is $18 million.Total Payout: The investor's total payout is $10 million (liquidation preference) + $18 million (participation) = $28 million.The Founder's Takeaway: This structure is less favorable for founders because investors double-dip, taking both their money back first and a proportional share of the remaining value. It significantly reduces the size of the payout for common shareholders, particularly in moderate-to-low-value exits. &nbsp; Key Differences and Founder's Action PlanNegotiate for Non-Participating: Always push for non-participating preferred stock. It is the industry standard for most early-stage venture capital. Look for a Cap: If an investor insists on a participating preference, try to negotiate a participation cap. A cap limits the total amount the investor can receive. For example, a "2x cap" means the investor's total return from the deal (liquidation preference + participation) cannot exceed twice their initial investment. This limits the investor's double-dipping and protects the founder's upside.

Understanding Participating v Non Participating Preferences: A Cheat Sheet for HealthTech Founders

Healthcare technology M&amp;A deals in Europe are facing a number of challenges that are causing them to fail or become more difficult to complete in the current market. While the sector remains attractive due to long-term trends like an aging population and the need for efficiency, several factors are creating a more cautious and complex environment for dealmakers.&nbsp;Here are the primary reasons why European healthcare technology M&amp;A deals are going wrong:1. Macroeconomic and Financial HeadwindsThe broader economic climate is a significant factor in deal failures.&nbsp;Higher Cost of Capital: Increased interest rates have made it more expensive for private equity firms and corporations to finance acquisitions, especially leveraged buyouts. This directly impacts deal valuations and can make some transactions financially unfeasible.Valuation Gap: A major issue is the mismatch between what sellers expect and what buyers are willing to pay.Sellers often have valuation expectations based on the high-flying market of 2021-2022. However, buyers are now more disciplined, prioritizing profitability and sustainable revenue models over rapid growth. This discrepancy often causes deals to collapse during due diligence.&nbsp; &nbsp; Shift to Profitability: Investors are less tolerant of companies that prioritize aggressive growth at the expense of profitability. Healthtech companies that scaled rapidly during the pandemic but lack a clear path to profitability are seen as less attractive targets, making it difficult for them to secure an exit.2. Regulatory and Data Privacy ComplexityThe highly regulated nature of healthcare, combined with a fragmented European landscape, creates significant hurdles.Data Privacy (GDPR): The General Data Protection Regulation (GDPR) is a major concern. Due diligence must be extremely thorough to ensure a target company is fully compliant with all data privacy regulations. Any significant gaps can be a deal-breaker, as breaches can lead to severe fines and reputational damage.Varying National Regulations: Unlike the more unified U.S. market, Europe is a patchwork of different countries with their own healthcare systems, reimbursement frameworks, and regulations. A healthtech product that is successful in Germany may not be compliant or reimbursable in France, adding complexity and risk to cross-border deals. Antitrust Scrutiny: Regulatory bodies are increasingly scrutinizing M&amp;A deals to prevent consolidation that could reduce competition and harm consumers.&nbsp;3. Integration and Operational ChallengesEven after a deal closes, the post-merger integration phase is fraught with risks.IT and System Interoperability: Integrating the complex IT systems of two healthtech companies, especially their electronic health records (EHRs) or billing software, is a massive technical challenge. Achieving seamless data flow and interoperability can be costly and time-consuming, diminishing the strategic value of the acquisition.Cultural and People Integration: Merging two companies with different cultures and operational styles can lead to internal friction and key personnel leaving. This is particularly relevant in the high-tech sector where talent is a critical asset.Diligence on Technology and AI: The rise of AI adds a new layer of complexity to due diligence. Buyers must carefully evaluate a target company's AI technology, ensuring it is compliant with emerging regulations and that its use is defensible and scalable.In summary, the European healthcare technology M&amp;A market is maturing, with a higher bar for success. Deals are no longer driven by a "growth at all costs" mentality. Instead, successful transactions require meticulous due diligence to navigate a fragmented regulatory landscape, a clear path to profitability, and a realistic valuation that accounts for the current economic environment.

Why do European Healthcare Technology M&A deals go wrong in today's market?

Unique and proprietary healthcare biomarker datasets are crucial for developing advanced AI and ML models that can discover new biomarkers, enhance diagnostics and create personalised treatment plans. These datasets provide a competitive advantage by offering specific, high-quality data that public datasets often lack, allowing for more precise and effective model training.Why Proprietary Datasets are a Game Changer While public datasets like those from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and The Cancer Genome Atlas (TCGA) are valuable for foundational research, proprietary datasets offer a distinct advantage. These unique data sets are often gathered through specific clinical trials, collaborations, or advanced lab testing, providing a more detailed and controlled view of a particular disease or patient population.Key characteristics of these valuable datasets include:Multimodal data: Integrating various data types like genomics (e.g., DNA, RNA), proteomics (e.g., proteins, peptides), metabolomics (e.g., metabolites), and medical imaging (e.g., MRI, CT scans) provides a holistic view of a patient's health.Longitudinal data: Datasets that track patients over extended periods offer insights into disease progression and treatment response, which is crucial for developing prognostic and predictive biomarkers.High-quality and curated data: Unlike raw data, which can be messy and inconsistent, proprietary datasets are often meticulously cleaned, harmonized, and annotated. This "AI-ready" data is essential for training robust and accurate models.Unique patient populations: These datasets can focus on rare diseases, specific demographics, or patients with particular genetic profiles, enabling the development of highly specialized AI models.Applications in Healthcare AIUsing unique biomarker datasets, AI and ML algorithms can unlock new possibilities in several healthcare domains.Biomarker Discovery: AI models can analyze complex, high-dimensional data to identify novel biomarkers that might be undetectable to human researchers. For example, machine learning algorithms can analyze patterns in wearable device data to detect early signs of cardiovascular problems.Personalised Medicine: By integrating genomic, clinical, and environmental data, AI can create a comprehensive patient profile. This allows for the selection of the most effective therapy and dosage for an individual, minimizing the "trial-and-error" approach to treatment.Diagnostics and Prognostics: AI-powered models trained on specific biomarker data can improve the accuracy of disease diagnosis and predict a patient's likely outcome. This helps clinicians make more informed decisions and plan timely interventions.Drug Discovery and Clinical Trials: AI can use biomarker data to simulate drug interactions, identify suitable patient cohorts for clinical trials, and predict the potential success of new drug candidates. This streamlines the drug development process, making it faster and more cost-effective.Email <a href="mailto:lloyd@nelsonadvisors.co.uk">lloyd@nelsonadvisors.co.uk</a> to discuss further.

Healthcare biomarker datasets enhancing AI models and ML algorithms

The intersection of private equity continuation funds and the healthcare technology sector is a particularly dynamic trend in 2025. This area is seeing significant activity driven by both the unique characteristics of health tech and the broader market forces shaping the private equity landscape.Here are the key trends for private equity continuation funds in healthcare technology in 2025:1. A Solution for Extended Value Creation in Complex MarketsHealthcare technology assets often require longer investment horizons than typical private equity investments. This is due to the time it takes to navigate:Regulatory Hurdles: Gaining approvals from bodies like the FDA and ensuring compliance with regulations such as HIPAA is a lengthy and complex process.Reimbursement Models: Establishing and scaling a profitable business model often depends on securing favorable reimbursement from private insurers and government programs (e.g., Medicare and Medicaid), which can take several years.Implementation and Adoption Cycles: Selling to large hospital systems or healthcare providers involves long sales cycles and slow integration processes.Continuation funds are a perfect fit for this scenario. They allow a GP to "hold and grow" a high-performing health tech company beyond the typical 10-year fund life. This gives the GP and the management team the necessary time to mature the company, secure regulatory approvals, and achieve a critical mass of adoption, ultimately positioning it for a more lucrative exit.2. Focus on "Crown Jewel" Digital Health AssetsPrivate equity firms are not using continuation funds to exit underperforming health tech companies. Instead, the trend is to move "crown jewel" assets into a new vehicle. These are companies with:Strong, recurring revenue models: Particularly those with a Software-as-a-Service (SaaS) component.Proven clinical efficacy: The technology has demonstrated a positive impact on patient outcomes or operational efficiency.Scalable platforms: The technology can be easily expanded to new markets or customer segments.Substantial growth potential: The company is well-positioned to capitalize on mega-trends like aging populations, telehealth, and value-based care.The continuation fund provides a fresh capital injection to fund strategic initiatives, such as tuck-in acquisitions to expand a company's offerings or to accelerate international expansion, further enhancing its value.3. AI and Data Analytics as Key DriversThe use of artificial intelligence (AI) and data analytics is revolutionizing healthcare, and this is a significant driver of continuation fund activity. PE firms are using these vehicles to back health tech companies that are:Developing AI-powered solutions: These could be for drug discovery, diagnostic tools, or administrative workflow automation.Leveraging large datasets: Companies that can effectively use patient data to improve care delivery or personalize treatments are highly sought after.Paving the way for new reimbursement pathways: Proposed legislation, such as the "Health Tech Investment Act," which aims to create a stable Medicare payment pathway for algorithm-based services, is de-risking investment in this space and making these companies more attractive for long-term holds. 4. Increased Scrutiny and Evolving GovernanceAs private equity's role in healthcare becomes more prominent, so does the scrutiny from regulators and the public. This is a crucial factor shaping continuation fund deals in 2025.State-level oversight: Several states are passing or considering legislation to regulate PE deals in healthcare, particularly those involving a "Management Services Organization" (MSO) model. This adds a layer of complexity and risk that needs to be carefully managed in a continuation fund's structure.Antitrust and fraud enforcement: Federal agencies are ramping up their enforcement actions against anti-competitive practices and healthcare fraud. GPs must ensure their health tech portfolio companies have robust compliance programs to mitigate these risks.Transparency and fairness: The established trend of using independent third-party valuations and advisory committees to ensure fair pricing and a smooth process for LPs cashing out is even more critical in the sensitive healthcare sector.In summary, continuation funds in healthcare technology are a powerful tool for private equity in 2025. They provide a mechanism to maximize the value of high-potential assets in a sector characterized by long development cycles and complex regulatory landscapes, while also addressing the growing need for liquidity and distributions to LPs. The focus remains on quality assets, particularly those leveraging AI and data, but the transactions are increasingly structured with heightened attention to governance and regulatory compliance.

Private Equity continuation funds trend in Healthcare Technology in 2025

Nelson Advisors: One of Europe's Leading Healthcare Technology Mergers and Acquisitions, Partnerships and Investment Advisory Firms

Nelson Advisors partners Lloyd Price and Paul Hemings interviewed by Mergermarket for their 'AI fuels European medtech M&amp;A despite regulatory uncertainty' story (<a href="https://mergermarket.ionanalytics.com/content/1004331406?source=news" data-mce-href="https://mergermarket.ionanalytics.com/content/1004331406?source=news">https://mergermarket.ionanalytics.com/content/1004331406?source=news</a>) Europe’s medtech M&amp;A activity is making a comeback as buyers clamour for artificial intelligence (AI) assets amid regulatory fragmentation and uncertainty.“With AI as the enabler, there’s a feeling companies don’t want to get left behind. You can’t sit on your laurels,” Lloyd Price, partner at the European healthtech M&amp;A advisor Nelson Advisors, told Mergermarket.One crucial consideration is the EU’s recent Medical Device Regulation and In Vitro Diagnostic Regulation, Paul Hemings, also partner at NelsonAdvisors, said. These measures have tightened requirements for clinical evidence, documentation, and post-market surveillance compared to before, often making development more costly and slower, he said.Despite the challenges, European medtech is attractive for M&amp;A as healthcare is seen as more resilient against macroeconomic headwinds compared to other industries, Price said.Sector end customers, which include insurers and public health systems, are generally reliable to work with, and M&amp;A is often the best way to enter the rigid world of procurement of equipment by national healthcare services, Price added.Cardiovascular disease therapies, robotics and AI drive dealmakingOne of the top killers in the world, cardiovascular disease is one of the hottest therapeutic areas for medtech M&amp;A, Price said, adding that wearables and remote monitoring devices are booming with an increasing focus on prevention.Another high-interest area is the use of robotics in pharmacies and remote surgery, Price said.The pipeline of expected deals in this space includes UK remote surgery developer CMR Surgical, which has reportedly engaged advisers to manage a potential sale of the business.The main buyers in Europe’s medtech scene include strategics such as Medtronic, Johnson &amp; Johnson, and Philips, which aim to diversify their core revenue streams, Hemings said. Private equity (PE) firms active in the space include Gilde Healthcare and Apposite Capital, he added.AI-powered startups have also become a big focus for investors, accounting for 65% of total equity funding in 1H25, even though only 40% of global healthcare startups currently deploy AI, according to Hemings.Strategics, including imaging specialists Siemens and Philips, have an appetite for AI to enhance image analysis and clinical workflows, Price said. Other buyers are tempted by the potential of AI to speed up the processing of notes and recordings in a clinical environment, he said.One recent example of the increasing AI focus is the buyout of the UK ophthalmology company Optegra by the French eyewear company EssilorLuxottica in May this year as part of a mission to power its procedures with AI, Hemings said.Meanwhile, PE buyers have previously aimed to merge companies into AI-based platforms or acquire next- generation software-as-a-service (SaaS) platforms, Hemings said.String of pearls approach amid tougher regulationsLarge buyers in medtech are increasingly branching out from big deals with late-stage companies to a series of smaller acquisitions in a “string of pearls” strategy, Hemings said.Examples include the US giant Johnson &amp; Johnson MedTech’s acquisitions of Abiomed (US), Laminar (US), Shockwave Medical (US) and V-Wave (Israel) in 2022, 2023, 2024 and 2024, respectively, according to a report by Nelson Advisors.This trend reflects a desire to avoid the risks of a huge buyout, including the costs of integration, rising staffing costs, uncertainties from fluctuating tariff policies, and regulatory fragmentation between different geographies, Price said.While the EU is attempting to streamline its regulatory and reimbursement processes, this has not yet been achieved and overseas players are thinking twice about operating in Europe, Pashazadeh said.However, these changes also drive M&amp;A demand for targets with expertise and a proven track record in navigating Europe’s regulatory environment, Price said.“At the end of the day, we're not really in the technology business; we're really in the business of behaviour change and trust,” he said.by Jonathan Smith with analytics by Kunal Samnani, Mergermarket<a href="https://info.mergermarket.com">https://info.mergermarket.com﻿</a>

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Understanding Participating v Non Participating Preferenc...

Why do European Healthcare Technology M&A deals go wrong ...

Healthcare biomarker datasets enhancing AI models and ML ...

Private Equity continuation funds trend in Healthcare Tec...

Nelson Advisors: One of Europe's Leading Healthcare Techn...

Nelson Advisors partners interviewed by Mergermarket - 'A...