The long-standing separation between research and financial performance in pharmaceutical and life sciences is breaking down. As capital becomes more selective and regulatory expectations rise, leaders are increasingly expected to hold scientific rigor and commercial accountability at the same time. “Scientific excellence is necessary but not sufficient for success,” says Vardan Ter‑Antonyan. “Holding P&L responsibility changes how you view R&D. It stops being an abstract innovation engine and becomes a capital allocation system.” Now Head of R&D at Mile High Labs, that perspective has been forged across a career spanning pharmaceutical, OTC and dietary supplement businesses, from early bench science to executive leadership.
As a site director at a contract laboratory and later as chief science officer within early stage science-led organizations, he reported directly to boards, managed multimillion-dollar budgets and owned forecasts subject to monthly scrutiny. That responsibility, while demanding, enforces a level of discipline that many science-driven organizations discover too late. “Every experiment, formulation or platform decision carries a financial impact,” he says. “Timing, scalability, yield and quality all show up later in cost of goods and speed to market. You either design for that reality early or you pay for it later.”
Why P&L Ownership Is So Hard in Science-Led Firms
Executive P&L ownership is uniquely challenging in scientific environments because of the shape of the value curve. Costs are immediate and visible, while returns are delayed, probabilistic and sometimes binary. Add regulatory complexity and quality risk, and accountability can easily fragment. Historically, many organizations insulated R&D from commercial pressure by treating it as a cost center. “Today, capital is more selective. Regulators expect robustness earlier. Markets want evidence of value, not just promise,” Ter‑Antonyan says.
Without true P&L ownership, organizations drift toward extremes. On one side is uncontrolled experimentation. On the other is short-term cost cutting that erodes long-term value. Purely financial leadership often defaults to cuts. Purely scientific leadership often defaults to spending. Neither works in isolation. The sustainable path is hybrid leadership that can make uncomfortable tradeoffs and defend them.
Turning Innovation Into Financial Performance
Across roles, Ter‑Antonyan has returned to three practices that consistently translate science into results. The first is portfolio-level thinking over project-level optimization. Strong leaders do not ask whether each project is perfect. They ask whether the portfolio is balanced across risk, time horizon and value. Stage gates matter only when they are real decision points, not reporting exercises. “You have to be willing to stop good science when the commercial logic no longer holds,” he says.
The second practice is explicit translation from science to P&L. Every major technical decision should map to a financial lever, whether time to market, yield, margin, quality cost or scalability. When teams understand how formulation robustness reduces scrap or how process simplicity lowers regulatory burden, rigor improves rather than erodes. Transparency aligns incentives. The third is separating controllable from allocated costs. Holding leaders accountable for economics they cannot influence damages trust and performance. High-performing organizations give science leaders clear line of sight into what they control, visibility into what is allocated and accountability for decisions.
The Shift Toward Continuous Decision Making
Looking ahead, Ter‑Antonyan sees executive P&L ownership becoming more dynamic. Forecasting and scenario analysis are moving from episodic exercises to continuous processes. AI-driven tools are beginning to collapse the distance between experimental data and financial insight, allowing leaders to see in near real time how changes in yield, stability or cycle time affect margin and cash flow. “P&L ownership becomes less about defending annual plans and more about steering under uncertainty,” he says. Probabilistic models, risk-adjusted values and options thinking will increasingly define leadership effectiveness. For science-led businesses, the future belongs to leaders who can integrate data, discipline and discovery without diluting any of them.
Follow Vardan Ter‑Antonyan on LinkedIn for more insights.
