The nonprofit American Association of Pharmaceutical Scientists (AAPS) will add two Innovator‑Curated tracks to its PharmSci 360 conference, set for October 25–28, 2026 in New Orleans, Louisiana. The sessions will examine research integrity in an AI era and showcase emerging methods that aim to replace animal testing in drug development.
Credibility and Open‑Science Track Highlights
On Monday, October 26, the first track will focus on credibility, reproducibility, and open‑science policy. Brian Nosek, co‑founder and executive director of the Center for Open Science, will anchor the day with a keynote urging greater openness and trust in research findings.
The morning symposium will feature panels on organizations that enable scientific fraud, the ability of publishers to catch problematic manuscripts, and lessons from large‑scale replication of preclinical cancer experiments. It will also discuss NIH initiatives to build a more reliable evidence ecosystem.
Maryam Zaringhalam of the Center for Open Science will moderate the symposium and a concluding session on open‑science policies designed to speed research translation. Sessions will explore methods for identifying problematic papers, verifying citations, and establishing ethical practices for using generative AI in research.
The agenda reflects growing concern that AI tools can both aid and obscure scientific rigor. By confronting these challenges, the track aims to provide concrete steps for researchers and institutions to safeguard the credibility of their work.
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Non‑Animal Drug Development Track Overview
Two days later, a full‑day track led by Johns Hopkins professor Thomas Hartung will showcase new‑approach methodologies (NAMs). Topics include human‑derived laboratory systems, AI applications, organ‑on‑a‑chip models, neural organoids, and computational models intended to reduce or replace animal testing.
The program arrives as federal agencies shift toward validation standards, targeted funding, and specific regulatory applications for NAM evidence. In March, the FDA issued draft guidance outlining four principles for such evidence during drug development.
The NIH has pledged $150 million over five years through its Complement‑ARIE program to develop and standardize human‑based research technologies. A morning symposium will cover neural microphysiological systems, regulatory data packages for organ chips, AI‑assisted chemical read‑across, and organoid intelligence.
Nicole Kleinstreuer, NIH Deputy Director, will deliver an afternoon keynote on building trust in non‑animal safety science. She will be followed by a session examining how startups, model developers, and regulators are approaching post‑animal drug development.
The organoid discussion ties directly to recent work from Johns Hopkins. Hartung and colleague Lena Smirnova coauthored a 2025 study reporting synaptic plasticity and other building blocks associated with learning and memory in human neural organoids.
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While the scientific community has long debated the reliability of animal models, the shift toward human‑based systems reflects a broader trend toward more predictive and ethical research. By aligning funding, guidance, and technology development, agencies hope to accelerate drug discovery while addressing public concerns about animal welfare.
The conference schedule feels a bit crowded, honestly, with back‑to‑back sessions that leave little room for informal networking. Yet the breadth of topics suggests AAPS is committed to covering both the philosophical and technical aspects of these emerging fields.
Attendees will also hear from industry representatives and regulatory officials about practical steps for integrating NAM data into filing packages. The goal is to create a clearer pathway for developers to demonstrate safety and efficacy without relying on traditional animal studies.
Overall, the two tracks aim to reinforce research integrity and promote innovative, humane drug development methods. The initiative highlights AAPS’s role in guiding the pharmaceutical community through a period of rapid technological change.
