Six Months Later: Neuland's Saharsh Davuluri Checks In on India, AI, and API Manufacturing

In this Part 1 of a two-part midyear 2026 follow-up interview, PharmTech reconnects with Saharsh Davuluri, Vice Chairman and Managing Director of Neuland Labs, to check in on predictions he made in a three-part interview last December covering geopolitical shifts, digital transformation, and the peptide/API sectors. Six months later, Davuluri finds his core theses largely holding up.

On manufacturing and geopolitics, Davuluri reports that despite global attention being consumed by the West Asia crisis in the first half of 2026, enthusiasm for India-based manufacturing has remained well-sustained, with growing reliance on India for API production. Neuland continues investing in large-scale peptide facilities, and demand for peptide manufacturing out of India keeps climbing. He reaffirms his December hypothesis that India will remain a critical global drug-manufacturing hub, noting the company is nearing several capacity milestones.

On digital transformation, Davuluri says Neuland is making steady progress toward the paperless, AI-enabled vision he described in December, though the gap between API manufacturing and more automated sectors hasn't fully closed. Neuland's near-term goal is a fully paperless R&D and process-development environment this year, eventually extending to pilot-scale and then commercial facilities, including the peptide plants currently being commissioned, which are being built with modern digital concepts baked in from the start. The company's new Hyderabad R&D campus remains on track for full readiness by November, with phased startups beforehand, and will pair AI tools with parallel synthesis equipment (eg, Radleys' Mya 4) discussed in the earlier interviews.

The biggest challenge, Davuluri says, isn't technical but human: change management. Training scientists to adopt and trust these new tools takes time—he estimates six to twelve months to build fluency—and Neuland is being deliberate about pacing that transition. He's also candid about the "rhetoric" around AI displacing workers, stressing that Neuland wants its scientific talent to see these tools as aids to their effectiveness rather than replacements, since morale and trust are as important to the rollout as the technology itself. Looking ahead, he targets sometime in 2027 for full-scale AI and automation in process development, underscoring that while the direction of travel from December remains unchanged, the human adoption curve—not the technology—is the pacing factor.