The following three parallel pre-conference courses are taking place on Monday 22nd September at the Hilton Hotel. View the details below or click here to download the programme schedule.

Please note that fees are £300 for those attending the full APACT Conference and £500 for those attending a course only. 

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Pre-conference courses - Monday 22 September 2025
Title Near-infrared hyperspectral imaging for quality assessment of tablets, powders and lyophilized products - Davinia Brouckaert, Indatech Non-linear Machine Learning for Calibration and Classification - Manny Palacios, Eigenvector Research Fundamentals of NIR PAT in Solid Dosage Pharmaceutical Manufacturing - Steve Hammond (Consultant) and Michael Reinhalter, Sentronic US Corp
Description Near-infrared spectroscopy (NIRS) is a popularly applied Process Analytical Technology (PAT) tool, due to its non-invasive and non-destructive nature, high versatility and reliability, as well as its broad applicability and cost-effectiveness. By adding spatial information, near-infrared chemical imaging (NIR-CI) adds value to benchtop NIR analysis, allowing to visualize the distribution of chemical components across the surface or volume of a sample. In the meantime, the fast acquisition speeds may transform the technology into an attractive tool for high-throughput in-line applications. In this course, the basics of NIRS and NIR-CI will be briefly tackled, before digging into more detail in the instrumentation, (dis)advantages and applications of the technology. Case studies from the pharmaceutical industry will be presented and discussed in detail, both on an R&D and an industrial manufacturing level. While linear machine learning methods, such as PLS regression, work in a very wide range of problems of chemical and biological interest, there are times when the relationships between variables are complex and require non-linear modeling methods. Many non-linear machine learning methods have been developed, however, we will focus on a few that we have found quite useful. The course begins with a discussion of linearizing transforms. Augmenting with non-linear transforms, e.g. polynomials, is discussed next. Locally Weighted Regression (LWR), Artificial Neural Networks (ANNs, including Deep-learning Networks) and Support Vector Machines (SVMs) are then considered, with SVMS for both regression and classification considered. Boosted regression and classification trees (XGBoost) and then covered. The course concludes with segments on how to choose a method and how to implement models online. The course includes hands-on computer time for participants to work example problems using PLS_Toolbox or Solo. This course seeks to provide attendees with an introduction to the theory and practice of near-infrared (NIR) spectroscopy applied to the analysis of solid samples in the pharmaceutical industry. The course will provide an overview of the fundamentals of NIR spectroscopy, discuss the challenges associated with analyzing and appropriately sampling streams of moving powders, provide an overview of common spectrometer and probe hardware used in the process environment, and introduce some common multivariate statistical methods used to extract process information from NIR spectra.
10.30 - 11.00 Registration
11.00 - 12.30
Introduction to NIR spectroscopy and hyperspectral imaging
Benchtop hyperspectral imaging
  • Instrumentation
  • Pros & cons
  • Applications
Introduction to Machine Learning
  • Nomenclature and Definitions
  • Methods: Unsupervised vs. Supervised
  • Bias vs. Variance Trade-off
  • Model Quality Metrics
Introduction to NIR and Sampling Fundamentals
  • Vibrational Spectroscopy Fundamentals
  • Diffuse Reflectance Fundamentals
  • Theory of Sampling Fundamentals
12.30 - 13.30 Lunch
13.30 - 15.00
Benchtop hyperspectral imaging
  • Industrial case studies
  • In-line multipoint NIR spectroscopy
  • Instrumentation
  • Pros & cons
Machine Learning Algorithms (Methods) - Part 1
  • Locally Weighted Regression
  • Support Vector Machines
  • Artificial Neural Networks
Chemometrics and NIR PAT Hardware
  • Chemometrics: Turning NIR Spectra into Process Information
  • Overview of Common Types of NIR PAT Systems
  • Discussion of spectrometer architecture
  • Discussion of process probes and their design
15.00 - 15.30 Tea & coffee
15.30 - 17.30
In-line multipoint NIR spectroscopy
  • Applications
  • Industrial case studies
Machine Learning Algorithms (Methods) - Part 2 & Conclusion
  • Gradient Boosted Decision Trees (brief overview)
  • Model Fusion (Model Ensembles)
  • Choosing the Right Method
NIR PAT Practical Session
  • Practical NIR PAT Considerations
  • Instructor-lead Hands-On NIR PAT Demonstration
  • Question and Answer Session
17.30 Closing remarks / end of course

 

Fees are £300 for those attending APACT Conference and £500 for those attending a course only. 

REGISTER NOW!