Very few people arrive at pharmaceutical manufacturing by way of clean energy and competitive badminton – where he reached a BWF World Tour ranking of 33. Hari Kiran Chereddi has done both. Today he is Founder, Managing Director and CEO of HRV Global LifeSciences (HRV Pharma) and New Horizon Global Pharma, where he has built something the industry is still learning to categorise: an asset-light, virtual API company that connects global generic manufacturers with certified production facilities without owning a single factory floor. Across more than two decades in clean energy, supply chain and pharmaceuticals, including co-founding Sujana Energy Limited and playing a key role in the Sriam Labs and Laurus Labs merger, he has developed a conviction that runs slightly against the grain of an industry built on brick, steel and installed capacity: the decisive advantage in manufacturing is shifting from what you own to what you can qualify, access and orchestrate.
That conviction is the subject of this conversation. We asked him what actually makes a site fit for a specific molecule, what must never change when a product moves between equipment trains and operators, why installed capacity and usable capacity are two very different numbers, how quality governance holds together when manufacturing, regulatory ownership and physical production sit in different organisations, and where AI, in the form of HRV’s reasoning system RIKO™, genuinely earns its place in the decision chain. His answers are a practical map of how a networked manufacturing model works when it is done properly, and where it quietly falls apart when it is not.
When manufacturing capacity is accessed through a network rather than a company-owned facility, what technical and quality criteria should determine whether a site is genuinely fit for a particular API or formulation?
I would begin by separating two ideas that the industry often treats as one: capacity and capability. In the evolving pharmaceutical landscape, manufacturing capability should not be evaluated only through the lens of available physical capacity. The more important question is whether the manufacturing partner has the right combination of technical capability, quality maturity, regulatory readiness and execution discipline required for a specific product. At HRV, we believe that a qualified manufacturing ecosystem is built around understanding the complete requirements of a product: from chemistry and process complexity to analytical needs, regulatory expectations, market requirements and supply reliability.
In practice, that means the assessment of a manufacturing partner runs across multiple parameters. We look at experience with similar molecules or formulations, regulatory history, quality systems, process understanding, analytical capabilities, equipment suitability, documentation practices and the demonstrated ability to consistently meet compliance expectations. Each of these tells you something the others cannot. Regulatory history tells you how a site behaves under scrutiny. Documentation practices tell you how it behaves when nobody is watching.
This is why a facility may have available capacity and still not be the right home for a product. True readiness depends on whether the site has the right processes, expertise and quality culture to manufacture a product successfully at scale, not just once, but batch after batch, campaign after campaign. The objective is not merely to identify available manufacturing capacity, but to create the right alignment between product opportunity, manufacturing capability and long-term market requirements. That alignment is not established in a single audit. It requires continuous technical engagement, ongoing partner evaluation and visibility across the entire product lifecycle.
How do you maintain process consistency when the same product moves across different manufacturing sites, equipment trains, utilities, operators and local operating practices? Which parameters are truly non-negotiable?
Consistency across multiple manufacturing locations depends on maintaining a common understanding of the product and the process, irrespective of where manufacturing takes place. The most important element is not replicating every physical aspect of a facility, which is rarely possible and often unnecessary, but ensuring that the scientific principles, process controls and quality expectations remain unchanged.
The non-negotiable parameters are clear. Critical quality attributes (CQAs) and critical process parameters (CPPs) do not move. Neither do raw-material specifications, analytical methods, impurity controls, documentation practices, deviation management or data integrity standards. Equipment, operators and local operating environments will differ from site to site, and that is acceptable. What cannot differ is the product’s quality requirements and the underlying process understanding that protects them.
Holding that line is an active exercise, not a documented assumption. It requires structured technology transfer, sustained technical engagement with manufacturing partners, periodic reviews and continuous monitoring of process performance. In a distributed manufacturing ecosystem, process knowledge becomes the anchor that maintains consistency. I would go further: the ability to transfer knowledge effectively across sites is as important as the physical manufacturing capability itself. A partner with excellent equipment and a weak transfer process will give you variability. A partner with modest equipment and disciplined process understanding will give you a product you can rely on.
In a brownfield environment, how should manufacturers assess the gap between available installed capacity and usable, validated capacity before committing a product to the site?
Installed capacity does not automatically translate into commercially usable capacity, and confusing the two is one of the more expensive mistakes in this industry. A manufacturing site may have all the required equipment on the floor, but the true question is whether the facility can consistently deliver the product within regulatory, technical and quality expectations.
Before committing a product, manufacturers need to work through a specific set of questions. Is the equipment genuinely suitable for this chemistry or dosage form? Is the process compatible with the existing train? What is the current validation status? Does the site have the analytical capability to support the product, and the utility requirements to run it? How does production scheduling look once this product is added? Is there sufficient quality bandwidth, and what regulatory commitments is the site already carrying?
The assessment should also extend across the complete product lifecycle, from technology transfer and validation batches through to consistent commercial production. A detailed gap assessment does more than produce a verdict. It tells you precisely what stands between installed and usable capacity, whether that is additional investment, process optimisation, operator training or further validation activities, and it lets you cost and schedule those gaps before a commitment is made rather than after. Capacity, in other words, should be viewed as a combination of infrastructure, capability and readiness, rather than simply available manufacturing space.
Where manufacturing, regulatory ownership and physical production sit with different organisations, how should responsibilities for process validation, change control, deviations, CAPA and data integrity be structured to remain inspection-ready?
A distributed pharmaceutical model requires a clearly defined governance framework, precisely because multiple stakeholders contribute to the final product outcome. The foundation is clarity of roles and responsibilities across product owners, manufacturing partners and other stakeholders, established through appropriate quality agreements, technical agreements and operating processes. These documents are not administrative overhead. They are the architecture of accountability.
Responsibilities related to process validation, change management, deviations, CAPA, documentation review and regulatory commitments must be established from the beginning, not negotiated during an investigation. While physical manufacturing may happen at a partner facility, quality cannot become fragmented across organisational boundaries. There needs to be continuous visibility, structured oversight and a clear escalation mechanism so that decisions affecting product quality and patient safety are managed appropriately and quickly, by the people who are accountable for them.
Data integrity is the other critical pillar. Complete traceability of manufacturing records, analytical results, quality decisions and process changes is essential for maintaining inspection readiness, and inspection readiness is not a state you can create in the weeks before an audit. It is the residue of how the ecosystem operates every day. The strength of a manufacturing network therefore depends not only on selecting capable partners, but on creating the right governance model to ensure accountability throughout the product lifecycle.
What tends to become the real bottleneck when scaling through external manufacturing capacity: equipment availability, technical transfer, analytical capability, batch-size economics, quality systems, regulatory commitments or supply-chain coordination? How have you seen these constraints play out in practice?
Scaling pharmaceutical products is rarely constrained by a single factor, which is what makes this question so interesting. The challenge usually lies in coordinating multiple interconnected activities across technical, commercial, quality and supply-chain functions. Capacity availability is the most visible challenge and therefore the one everyone plans around, but the actual bottlenecks frequently emerge elsewhere: during technology transfer, in analytical alignment, in documentation readiness, in quality-system maturity and in regulatory execution.
The pattern we see repeatedly is a site with entirely adequate infrastructure that still struggles at commercial scale-up, because the process understanding, analytical capability or quality discipline has not travelled with the product. Supply-chain coordination compounds this as volumes grow, since companies are then managing raw materials, manufacturing timelines, testing cycles, regulatory requirements and customer commitments across multiple stakeholders at once, each with its own clock.
The advantage of a networked model is flexibility. Companies can access specialised capabilities without creating unnecessary fixed infrastructure, and without carrying that infrastructure through the quieter parts of a product cycle. But flexibility is not free. It demands strong intelligence, transparency and coordination to work. Our focus at HRV has been to solve exactly this coordination challenge, by combining manufacturing partnerships, regulatory expertise, product intelligence and technology-enabled visibility across the pharmaceutical value chain.
For a networked manufacturing model to work at scale, what digital infrastructure is actually necessary across sites? Where can MES, electronic batch records, real-time data, predictive analytics or AI add operational value, and where is digitalisation still secondary to disciplined process control?
Digital transformation in pharma will create value only when it improves decision-making. Digitising an existing process without changing the quality of the decisions it supports is activity, not transformation. For a networked pharmaceutical model, the foundation is visibility: across customers, products, suppliers, manufacturing partners, regulatory requirements, quality indicators and commercial opportunities.
Technologies such as MES, electronic batch records and real-time monitoring have a clear role here, and they strengthen traceability and operational control in ways that are difficult to achieve on paper. But the larger opportunity lies further upstream, in using intelligence to anticipate challenges before they occur rather than documenting them accurately after they have.
At HRV, RIKO™ represents this approach. It is an AI reasoning system built from HRV’s operational experience across commercial evaluations, regulatory strategy, chemistry assessments, quality investigations, supplier performance, licensing decisions, audit outcomes and global supply execution. The platform evaluates risk and reliability signals across chemistry, regulatory history and supplier performance before critical decisions are made, at the point where those decisions are still inexpensive to change.
Having said that, technology remains an enabler and nothing more. Strong processes, quality culture, regulatory discipline and partner governance remain the foundation, and no analytics layer will compensate for their absence. The real opportunity is not replacing human judgement but compounding it, turning what individuals in the organisation have learned into institutional intelligence that the next decision can draw on.
If pharma manufacturing increasingly shifts from owning physical capacity to accessing qualified capacity, what changes in the way companies should think about capacity planning, technology transfer, validation and long-term supply assurance?
The industry is moving towards a model where access to capability, intelligence and specialised expertise will matter as much as physical ownership. The future competitive advantage may not come only from owning more assets, but from making better decisions across a wider ecosystem of capabilities. That reframes several things at once.
Capacity planning becomes a question of partner capability, regulatory readiness, technology-transfer expertise and supply resilience, rather than a calculation based purely on internal infrastructure. Technology transfer stops being a project activity and becomes a strategic capability in its own right, because knowledge, process understanding and quality expectations have to move effectively across organisational boundaries, repeatedly and reliably. Validation and supply assurance shift from milestone events to continuous disciplines, requiring ongoing oversight, active risk management and genuine collaboration between stakeholders who may sit in different companies and different countries.
At HRV, we believe the next phase of pharmaceutical growth will be driven by intelligent orchestration: combining regulatory expertise, product understanding, technology and strategic partnerships to build supply ecosystems that are both scalable and resilient. Ownership will always have its place. But the companies that learn to orchestrate well will find they can move faster, into more markets, with less capital tied to the ground.
About the Guest
Hari Kiran Chereddi is the Founder, Managing Director and CEO of HRV Pharma, also known as HRV Global LifeSciences, and of New Horizon Global Pharma. A global business leader and entrepreneur with more than 20 years of experience across clean energy, supply chain management and the pharmaceutical sector, he leads HRV as an asset-light, virtual active pharmaceutical ingredients (API) company that connects global generic drug manufacturers with certified production facilities without owning physical factories. He previously co-founded Sujana Energy Limited, scaling it into one of India’s leading clean energy innovators, and played a key role in the Sriam Labs and Laurus Labs merger. Hari is a Harvard Business School alumnus and a former professional badminton player who reached a career-best world ranking of 33 on the BWF World Tour; he is also a member of the Forbes Global CEO council.
Disclaimer: The views and opinions expressed in this editorial are those of the interviewee and are based on his professional experience across pharmaceutical supply chains, networked manufacturing, regulatory strategy and technology-enabled operations. They do not necessarily reflect the official views, policies, or positions of Hello Pharma, its management, or its affiliates. Hello Pharma does not endorse or take responsibility for any specific technical, commercial, or regulatory interpretations presented in this article. Readers are encouraged to independently evaluate the information shared, review applicable regulatory guidance, and rely on their own experience, expertise, and professional judgement before making decisions related to manufacturing strategy, partner selection, technology transfer, or regulatory compliance.
