Daily biotech intelligence: FDA actions, drug recalls, and recent research.
ZOLEDRONIC ACID — Approved Sponsor: MYLAN LABS LTD · Application type: SUPPL · Date: 20230307 · Priority: STANDARD
LAMOTRIGINE — Approved Sponsor: ALEMBIC PHARMS LTD · Application type: SUPPL · Date: 20160902 · Priority: STANDARD
ABREVA (DOCOSANOL) — Approved Sponsor: HALEON US HOLDINGS · Application type: SUPPL · Date: 20021213 · Priority: STANDARD
LURASIDONE HYDROCHLORIDE — Approved Sponsor: TORRENT · Application type: SUPPL · Date: 20260413 · Priority: STANDARD
SPRAVATO (ESKETAMINE HYDROCHLORIDE) — Approved Sponsor: JANSSEN PHARMS · Application type: SUPPL · Date: 20220103 · Priority: N/A
Unknown — Approved Sponsor: AMIVAS · Application type: SUPPL · Date: 20230303 · Priority: STANDARD
Unknown — Approved Sponsor: NOVITIUM PHARMA · Application type: ORIG · Date: 20260413 · Priority: STANDARD
FILSPARI (SPARSENTAN) — Approved Sponsor: TRAVERE · Application type: SUPPL · Date: 20231018 · Priority: N/A
MILNACIPRAN HYDROCHLORIDE — Approved Sponsor: BRECKENRIDGE · Application type: ORIG · Date: 20160127 · Priority: STANDARD
DANZITEN (NILOTINIB) — Approved Sponsor: AZURITY · Application type: ORIG · Date: 20241107 · Priority: STANDARD
Appco Pharma LLC [Class II] — 20260408 Product: Prazosin Hydrochloride Capsules, USP, 1mg, 100-count bottle, Rx Only, Manufactured for: Biocon Pharm Reason: cGMP deviation: detection of Nitrosamine Drug Substance-Related Impurities, N-nitroso-prazosin impurity C (NNP) above acceptable limits.
Amneal Pharmaceuticals, LLC [Class II] — 20260408 Product: traMADol Hydrochloride Tablets, USP, 50 mg, 500-count bottles, Rx only, Manufactured by: Amneal Pha Reason: Failed Impurities/Degradation Specifications: N-nitroso-desmethyl-tramadol impurity (NDSRI) was found out of the specification at 24-month stability i
Appco Pharma LLC [Class II] — 20260408 Product: Prazosin Hydrochloride Capsules, USP, 2mg, 100-count bottle, Rx Only, Manufactured for: Biocon Phar Reason: cGMP deviation: detection of Nitrosamine Drug Substance-Related Impurities, N-nitroso-prazosin impurity C (NNP) above acceptable limits.
K.C. Pharmaceuticals, Inc [Class II] — 20260408 Product: Artificial Tears Sterile Lubricant Eye Drops (polyvinyl alcohol 0.5%, povidone 0.6%), 0.5 FL OZ (15 Reason: Lack of Assurance of Sterility
K.C. Pharmaceuticals, Inc [Class II] — 20260408 Product: Ultra Lubricating Eye Drops (polyethylene 400 0.4%, propylene glycol 0.3%), Sterile, 0.5 FL OZ (15mL Reason: Lack of Assurance of Sterility
Sean Hill, Felix X. -F. Ye · 2026-04-17 · cs.LG · math.DS
Stochastic dynamical systems with slow or metastable behavior evolve, on long time scales, on an unknown low-dimensional manifold in high-dimensional ambient space. Building a reduced simulator from short-burst ambient ensembles is a long-standing problem: local-chart methods like ATLAS suffer from exponential landmark scaling and per-step reprojec
Shriram Chennakesavalu, Kirill Shmilovich, Hayley Weir · 2026-04-17 · cs.LG · physics.chem-ph
Large Language Models (LLMs) have the potential to accelerate small molecule drug design due to their ability to reason about information from diverse sources and formats. However, their practical utility remains unclear due to the lack of benchmarks that reflect real-world scenarios. In this work, we introduce a suite of chemically-grounded tasks
Yunhe Li, Hao Shi, Bowen Deng · 2026-04-17 · cs.AI · cs.CL
Although most of the automated theorem-proving approaches depend on formal proof systems, informal theorem proving can align better with large language models' (LLMs) strength in natural language processing. In this work, we identify a primary bottleneck in informal theorem proving as a lack of insight, namely the difficulty of recognizing the core
Aswathi Mundayatt, Jaya Sreevalsan-Nair · 2026-04-17 · cs.LG
Existing multi-hazard susceptibility mapping (MHSM) studies often rely on spatially uniform models, treat hazards independently, and provide limited representation of cross-hazard dependence and uncertainty. To address these limitations, this study proposes a deep learning (DL) workflow for joint flood-landslide multi-hazard susceptibility mapping
Seulgi Kim, Mohit Prabhushankar, Ghassan AlRegib · 2026-04-17 · cs.CV · cs.LG
Vision Language models (VLMs) have demonstrated strong performance across a wide range of benchmarks, yet they often suffer from modality dominance, where predictions rely disproportionately on a single modality. Prior approaches primarily address this issue by steering model's attention allocation, implicitly assuming that all modalities provide s
Sarthak Mittal, Leo Gagnon, Guillaume Lajoie · 2026-04-17 · cs.LG · cs.AI
Frontier models have demonstrated exceptional capabilities following the integration of task-reward-based reinforcement learning (RL) into their training pipelines, enabling systems to evolve from pure reasoning models into sophisticated agents. However, debate persists regarding whether RL genuinely instills new skills within a base model or merel
Ishaan Madan, Ben K. D. Pearce · 2026-04-17 · astro-ph.EP · physics.chem-ph
Saturn's moon Titan is a prime destination for investigating prebiotic chemistry beyond Earth, particularly at impact crater sites where transient liquid water may have enabled aqueous reactions between organic molecules. Selk crater represents one such environment and is a primary target of NASA's Dragonfly mission. Here, we present a thermodynami
Habibeh Naderi, Behrouz Haji Soleimani, Stan Matwin · 2026-04-17 · cs.LG · cs.AI
We propose HILBERT (HIerarchical Long-sequence Balanced Embedding with Reciprocal contrastive Training), a cross-attentive multimodal framework for learning document-level audio-text representations from long, segmented sequences in low-resource data settings. HILBERT leverages frozen pre-trained speech and language encoders to extract segment-leve
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