CORTEXA
← Browse
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26Cited by 0

Ftir Spectroscopy In Pharmaceutical Research And Quality Control: A Comprehensive Review

Shashank Tiwari

FTIR spectroscopy: one of the most powerful vibrational spectroscopic techniques used in pharmaceutical research, formulation development and quality control. In brief, the method relies on the interaction of infrared light with molecular vibrations that result in distinct absorption spectra or chemically specific molecular fingerprints. FTIR quickly gave rise to the new gold standard for analysis as it requires little sample preparation, is a non-destructive method and has an excellent reproducibility which makes FTIR an essential analytical tool across all stages in the life cycle of pharmaceutical products. It finds applications in the identification of active pharmaceutical ingredients (APIs), characterization of excipients, drug-excipient compatibility studies, polymorphism analysis, stability testing as well as counterfeit medicine detection, herbal drug authentication and quality assurance on finished formulations.Recent advances in technology such as Attenuated Total Reflectance (ATR)-FTIR, FTIR microscopy, portable spectrometers and chemometric modelling/artificial intelligence (AI) have greatly broadened the analytical scope of FTIR spectroscopy. In addition to FTIR, the combination with Process Analytical Technology (PAT), Quality by Design (QbD), and continuous pharmaceutical manufacturing allows researchers to monitor critical quality attributes of samples in real-time, resulting in improved manufacturing efficiency, product consistency, and compliance with regulatory guidelines. Moreover, machine learning and deep learning algorithms have turned FTIR into a smart analytical platform suitable for automatic spectral analysis, predictive quality assessment, and optimization of processes.This review highlights various aspects as brief outlines detailing the principles, instrumentation, sampling techniques, pharmaceutical applications, quality control strategies, regulatory perspectives and recent technological advances of FTIR spectroscopy along with future prospects. Additionally, the review further emphasizes the increasing applicability of FTIR in intelligent pharmaceutical manufacturing and discusses new prospects for implementing artificial intelligence, digital twin cloud computing and autonomous quality control systems into modern pharmaceutical analytics.

View free PDFSource page

Related papers

openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25

# Artificial Intelligence in Metallurgical Engineering: A Comprehensive Review of Applications, Challenges, and Future Direction

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Transformation in Metallurgical Engineering: From Microstructure Analysis to Smart Manufacturing and Sustainable Production"** ### Alternative Title 2 (Process-Focused)**"Machine Learning and Deep Learning…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-25

# Artificial Intelligence-Enabled Quantification of Cube and Goss Textures in Polycrystalline Materials: A Comprehensive Review of Machine Learning, Deep Learning, and EBSD-Based Characterization Approaches

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-08-15

Deep Learning for Human Activity Recognition: A Comprehensive Review of Architectures, Performance, and Challenges Across Five Sensory Datasets

Abeer FathAllah Brery, Ascensión Gallardo-Antolín, Mahmoud Fakhry, Israel Gonzalez-Carrasco

Human activity recognition (HAR) using sensor data allows the automatic detection of human behavior and actions in everyday environments. The development of scalable and privacy-preserving HAR systems is supported by the nonintrusive collection of time-series data using wearable…

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

Artificial Intelligence In Pharmaceutical Process Validation: A Review

Taufik Mulla*, Siddheshwar Sonavane, Ayush Tambe, Megha Hange, P. N. Sable

For decades, pharmaceutical process validation has rested on a relatively narrow set of habits: a fixed qualification protocol, a small handful of conformance batches, and a periodic review of trends to argue that manufacturing is operating consistently. That posture is being cha…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

Controllable Generative AI: A Technical Review of Model Parameters for Hallucination Mitigation, Fine-Tuning, and Replicable Model Construction

Prateek Dutta

Generative artificial intelligence (GenAI) systems, particularly large language models (LLMs), expose a dense and interacting set of architectural, optimization, and inference-time parameters that jointly determine factual reliability, adaptation quality, and reproducibility. Thi…

View free PDFSource page