Hitesh Vachharajani Vachharajani on why customer proximity, operational reliability and business-model redesign will determine who creates value in life sciences
Hitesh Vachharajani has spent 27 years across pharmaceuticals, medtech and diagnostics, working in Australia, New Zealand, India, the United Kingdom and parts of the United States. His experience spans strategy, mergers and acquisitions, portfolio management, operational transformation and business-process reinvention, and he now applies that perspective as the founder of Enteliqo, which is developing a breath-based diagnostic for early detection of diseases including Alzheimer’s and Parkinson’s.
That combination of incumbent experience and startup responsibility has shaped Hitesh’s view of the life sciences sector. He sees an industry under pressure from chronic disease, ageing populations, workforce burnout, affordability constraints and the digitisation of healthcare, but he also sees an opportunity for companies willing to reconsider how value is created rather than simply improving existing activities.
Value is moving beyond low cost and technical novelty
In generic pharmaceuticals, the traditional growth formula has been broad distribution, low cost and scale. Hitesh believes value creation is moving towards more complex generics, injectables, biosimilars, hospital and specialty therapeutics, where supply reliability and portfolio discipline matter more than simply offering the lowest price.
Reliability has become part of the value proposition because a missing critical product can disrupt a major procedure, create problems for hospitals and ultimately harm patients. In that environment, operational excellence is not only an internal capability. It can become a commercial advantage, particularly when procurement decisions have historically focused too narrowly on price and volume.
That logic also changes how companies allocate capital. Hitesh argues that what a company chooses not to do can be as important as the initiatives it pursues, because fragmented portfolios and poorly chosen investments consume resources without creating a distinctive position. The companies that prosper will not necessarily be the cheapest, but those that make more deliberate choices about where they can create value differently.
For innovative pharmaceutical companies, the source of value is also broadening beyond research and late-stage clinical trials. Comparative value against established practices, evidence from real-world use, early health technology assessment, hospital adoption and patient adherence all influence whether an innovation can achieve meaningful access.
Medtech presents a similar divide. Consumables such as gloves and gowns remain largely commodity businesses in which scale, price and volume dominate, although environmental sustainability is becoming more significant. Innovator products, including implants and devices used in orthopaedics, cardiology and neurology, must demonstrate clinical and workflow fit by helping clinicians save time, reduce friction and improve patient outcomes.
AI amplifies the process a company already has
Hitesh sees artificial intelligence as a horizontal force that will affect almost every part of the pharmaceutical value chain, from procurement and manufacturing to finance, human resources, marketing and supply chain management. The breadth of that opportunity, however, creates a strategic risk: companies may apply AI to existing processes without asking whether those processes remain relevant.
His warning is direct: AI does not repair a broken process; it amplifies it. A company might use AI to improve call planning for a sales structure designed for an earlier market, automate conversations that physicians do not want to have, or produce medical content faster without changing the underlying approach to professional engagement.
The more consequential question is whether AI can enable something the organisation could not do before. That might involve removing the traditional sales-representative model in selected therapeutic areas, using digital signals to predict healthcare-professional engagement and retention, or improving supply-chain forecasting in ways that increase both customer satisfaction and financial performance.
Hitesh distinguishes between an efficiency play and a strategic play. Automating repetitive work so employees can focus on higher-order tasks may be worthwhile, but the larger opportunity comes from reconsidering the commercial model, identifying changing customer needs and then deciding where AI can enable a different form of value creation.
That requires leadership to establish a clear roadmap, select a focused starting point and define how success will be measured. Hitesh favours early, affordable mistakes and rapid learning rather than large investments whose benefits cannot be isolated, because without visible early wins, enthusiasm for AI can quickly become another organisational initiative that stakeholders learn to disregard.
Healthcare is moving closer to the patient
The pressures facing health systems are not limited to technology. Hitesh points to the growing chronic disease burden, ageing populations, workforce burnout, fragmented digital systems and the need for both financial and environmental sustainability. Interoperability, cybersecurity and privacy remain practical obstacles, as health systems attempt to connect records and workflows that have often been unable to communicate effectively.
These pressures are accelerating a movement of diagnosis and care away from specialist hospitals and towards communities and patients’ homes. Wearable devices, machine learning, telemedicine and other monitoring technologies can support earlier detection and treatment while improving access for people who live far from specialist services.
Hitesh’s work in Alzheimer’s research illustrates the access problem. He notes that Australia has far fewer neurologists than are needed, with most specialists concentrated in major cities, leaving rural communities with poorer access to diagnosis and treatment. Technologies that allow clinicians to monitor patients remotely could improve equity while reducing the cost and delay associated with centralised care.
The same movement is changing the role of diagnostics and earlier detection can influence the subsequent therapeutic pathway, identify appropriate participants for clinical trials and support faster treatment decisions. Hitesh is building Enteliqo as a platform that begins with neurodegenerative disease and could extend into cancers, because he sees broader value in a diagnostic capability that can be applied across multiple disease areas rather than a single product.
He also expects more progress to come from the intersection of disciplines. Combining expertise and data from areas such as proteomics and genomics can accelerate precision medicine, while the involvement of data scientists and clinicians can shorten the path from complex biological information to a usable diagnosis. The commercial opportunity lies in integrating these capabilities around a patient and system need, not in preserving disciplinary boundaries.
The development cycle can be compressed, but regulation still matters
Hitesh sees several forces shortening the time required to develop and bring new healthcare products to market. Digital tools can improve patient recruitment for clinical trials, while machine learning can accelerate data capture, analysis and decision-making during the trial process.
Generative AI is also being used to identify potential molecules based on desired benefits and unwanted side effects, reducing the time required to produce initial candidates. Digital models, robotic simulations and human tissue models may further compress preclinical development, while reducing reliance on animal studies.
These developments do not remove the need for regulatory discipline, but they may change how regulators evaluate and process innovation. Hitesh points to increasing collaboration among regulatory bodies as they learn how to assess new technologies and consider how AI might support faster approvals without abandoning the requirements of safety and evidence.
The potential effect is cumulative and faster discovery, more efficient preclinical work, improved patient recruitment and accelerated clinical analysis could reduce development time across several stages, although Hitesh expects the most visible benefits to emerge over the next three to five years rather than immediately.
For established companies, the strategic question is not simply how to invest in each new tool. It is how to redesign the development and commercial system so that technology, clinical evidence, payer requirements and patient access reinforce one another.
Customer proximity is the discipline incumbents find hardest to institutionalise
Hitesh’s approach to building Enteliqo begins with direct contact with the people affected by the problem. He has personally interviewed more than 300 neurologists, clinicians, regulators and payer representatives, and spent time in aged-care settings to understand not only the patient experience but also the effect of Alzheimer’s on families, funding systems and care providers.
That research shaped the product before the technology was fully designed. It also helped identify who holds influence, who makes decisions, who pays and how the product would need to fit into the broader healthcare system. For Hitesh, customer proximity is therefore more than a source of market insight. It is a way to understand the economics and power structure that determine whether an innovation can survive.
He has applied the same discipline to the company’s cost structure. Rather than building a large, fixed organisation, Enteliqo uses a network of specialists across accounting, legal work, intellectual property, regulatory strategy and clinical strategy. This approach reduces fixed costs while giving the company access to capabilities and practices that would be difficult to develop internally at its current stage.
The lesson extends to larger pharmaceutical companies, where selected activities such as pharmacovigilance, regulatory affairs and quality assurance may be handled by specialist partners when doing so supports the company’s strategy. The point is not outsourcing for its own sake, but the deliberate use of external capability to remain focused, flexible and relevant.
Hitesh believes incumbent organisations can adopt the same mindset if they institutionalise customer contact beyond the sales function. An example from his early career involved back-office employees meeting their counterparts in hospitals, enabling supply-chain managers and other internal specialists to understand the customer’s operating reality directly rather than relying on second-hand information.
That discipline supports what Hitesh describes as a clear separation between where a company plays and how it plays. The former concerns markets, customers and disease areas; the latter concerns the value proposition, operating model and capabilities used to win. AI can strengthen either dimension, but it cannot decide the strategic question on the company’s behalf.
The strongest organisations will combine customer understanding with ruthless prioritisation, early attention to clinical and economic value, and a willingness to change established models. Hitesh’s experience suggests that life sciences companies do not need to abandon their incumbent strengths, but they do need to build the habits of a challenger before external pressure forces them to do so.