Abstracts

Genomics Studio (2026-US-PO-2888) The rapid growth of high-throughput omics technologies has created a need for integrated, user-friendly tools that enable robust and scalable analysis of complex biological data. In JMP Pro 20, we introduce the Genomics Starter, a structured and intuitive interface designed to streamline end-to-end workflows across genomics, transcriptomics, and microbiome studies.Inspired by the familiar JMP Start...

Skill level: intermediate

Farzaneh Rastegari and others

JMP Bayesian Optimization Case Study with Complex Formulation Constraints (2026-US-PO-2981) Bayesian optimization is a powerful statistical approach that accelerates discovery in molecules, formulations, products, packaging, and processes by efficiently guiding sequential experiments, making it ideal for costly or time-consuming studies. This presentation demonstrates the applications of JMP Bayseian Optimization to optimize product and formulation design. We showcase a complex case study...

Skill level: advanced

Fangyi Luo and others

Defining Optimal Operating Regions in Process Validation (2026-US-30MP-2965) Process validation, such as Quality by Design (QbD) approaches, relies on designed experiments to understand process behavior and define optimal operating regions. These efforts commonly progress from scouting and screening studies to response surface methods, with regulated industries requiring clear definition of Proven Acceptable Ranges (PARs) for Critical Process Parameters (CPPs).At Gore, we a...

Skill level: intermediate

John Szarka W. L. Gore & Associates

Structuring Curve and Spectral Instrument Data for Exploration and Modeling (2026-US-30MP-2923) Instruments often primarily designed for data collection produce rich curve and spectral‑based data, but their associated software typically supports only limited, domain‑specific analysis. Once loaded into JMP, even small changes in how the data is structured can enable far more flexible and interactive analysis.This presentation shows how JMP is used interactively to structure instrument output i...

Skill level: intermediate

Ryan Cooper and others

Functional Data Meets Mixture DOE in a Food Production Case Study (2026-US-30MP-2974) Food texture plays a critical role in consumer acceptance, requiring careful control of viscosity to achieve the desired sensory experience. At the same time, food and beverage manufacturers must ensure products can be processed efficiently to minimize waste while maintaining quality and affordability. Achieving this balance becomes especially challenging when formulation changes are required.This ...

Skill level: intermediate

Curtis Park HP Hood

A Discrete Event Simulation Add-in for JMP (2026-US-PO-2886) This paper presents a Discrete Event Simulation (DES) add‑in for JMP that enables users to model, analyze, and optimize complex process flows through an intuitive graphical interface. The add‑in provides a fully integrated GUI that allows users to construct simulations using configurable entity sources, queues, and processes. Entity sources support variable release timings, enabling realistic model...

Skill level: beginner

Jerry Fish JMP

Virtual Component Pairing for High-Precision Optical Modules via MVR Model (2026-US-PO-2915) In high-precision optics manufacturing, dual-component module assembly faces significant yield challenges due to the complex interplay between component tolerances and final performance. Current inefficiencies stem from poor pairing and uncertain specification limits, necessitating a resource-intensive "mix-and-match" bottleneck that results in substantial labor and material losses.This paper prese...

Skill level: intermediate

Weonwoo Kim MKS INSTRUMENTS

Demystifying the Bayesian Optimization Platform in JMP Pro (2026-US-30MP-2942) While the JMP Bayesian Optimization platform’s Auto Mode conveniently automates the sequential experimentation process for the most common applications, working directly with candidate sets and the Augmented Acquisition Functions Profiler in Custom Mode opens the possibility of more user-driven Bayesian optimization.We explain the meaning of the different acquisition functions, along with how and w...

Skill level: intermediate

Kasia Dobrzycka JMP

Let it Be (Done Already): Saving Time with Sequential Sampling (2026-US-30MP-2897) Sequential sampling is like a relationship. After a while, we can either accept it, reject it – or keep trying. Compared to its stodgy cousin, fixed size sampling, we are nimbly making a decision every step of the way. This method has a very big advantage over the fixed size approach: it often requires far fewer parts, yet provides the same statistical power. Fewer parts means it saves time, m...

Skill level: intermediate

Charlie Whitman JMP

Finding the Sweet Spot: Cross-Product Analytical Optimization in Biopharmaceutical Development (2026-EU-30MP-2788) In biopharmaceutical development, a recurring challenge is determining how analytical insights can be leveraged to establish and optimize methods. This case study focuses on a specific chromatographic technique, with the underlying approach having been successfully applied in other areas such as formulation and bioprocess development.To address this task, data from individual design of experiments ...

Jan Spindler

Application of Several JMP Tools for Process Improvement: A Purification Case Study (2026-EU-30MP-2782) This presentation demonstrates how JMP tools support process optimization and online NIR implementation for reliable product quality monitoring. It includes a case study in which SPC and capability analysis are applied to assess product purity, while process control ranges are defined using DOE, Genreg/SVEM modeling, and the Design Space Profiler. For NIR-based purity modeling, PCA and FD...

Frank Deruyck and others

Data Analysis, Generative AI, and the Human Factor (2026-EU-30MP-2804) Remember when machine learning was the next big thing, and after that, data mining? Each time, the end of statistical modeling was predicted – wrongly so. Now, what about the impact of generative AI on statistical data analysis? Can we leave data analysis to AI? Should we, perhaps, stop teaching applied statistics to scientists and engineers? In this presentation, we test the capabilities of ...

Skill level: beginner

David Meintrup

Temporal Profile Predictions for Cell Culture Using FDE and PLS (2026-EU-30MP-2778) Managing cell culture operations during bioreactor experiments is demanding, requiring constant adjustment. Coordination with downstream purification and analytics adds complexity, where misalignment drives inefficiency and delays. These challenges are magnified during technology transfer, where scale, equipment, and operational differences introduce additional uncertainty.To mitigate these ch...

Skill level: advanced

Per Vase and others

Applying DOE to Large Language Models (2026-EU-30MP-2761) ChatGPT, and large language models (LLM) in general, have become a growing source of information. The caveat is that their responses need to be assessed before being used, so that the emphasis moves from efforts to generate information to efforts to assess the quality of information. In this talk we move the attention, yet again, to the design of prompts used to learn from LLM platforms. We apply J...

Ron Kenett and others

Head to Head: Optimal DOE vs. Bayesian Learning for LCMS Assay Development (2026-EU-30MP-2771) Developing multiple drugs of abuse testing (DAT) assays in parallel for the cobas® Mass Spectrometry system demands an efficient optimization workflow. This talk details our approach to optimizing the HPLC gradient, a typical challenge with a vast factor space in LCMS method development. We began with a constrained, I-optimal designed experiment of over 80 runs to generate the rich data set needed ...

Sebastian Hoffmeister

Hybrid Modelling and Other Practical Strategies for Modelling Real Data (2026-EU-PO-2863) This poster highlights several practical strategies adopted over the years to make models more applicable to real systems. For a model to be useful, it must be representative of a system. And for the model to be widely adopted, users need to trust the model. Even though JMP has a lot of great platforms and techniques to model data, the model obtained is not always fully representative of the realit...

Pilar Gomez Jimenez

Modeling Synthetic Chromatograms in JMP 19: Updates and New Applications (2026-EU-PO-2745) Chromatographic techniques such as HPLC, GC, and CGE are essential for analytical workflows across industries. However, optimizing these methods remains challenging due to numerous parameters and the complexity of chromatograms. Traditionally, performance metrics such as resolution or peak-to-valley ratios are extracted and modeled, but linking these metrics back to the full chromatogram is often d...

Skill level: advanced

Marco Kunzelmann

Multiple Trend Optimisation with JMP Functional Data Explorer (2026-EU-30MP-2860) A good small-scale model (SSM) is a process performed at laboratory scale, representing a manufacturing-scale process. Establishing an SSM that is truly representative of manufacturing scale is integral to allowing small-scale process characterisation studies. Previously, the analysis of time-course data was performed with an approach that assessed ±3 SD of the mean manufacturing data, though somet...

Gwenola Ninon

Accelerating Power MOSFET Development Using TCAD Simulations and JMP Bayesian Optimization (2026-EU-PO-2837) In the fast-paced development of new power device technologies, defining and validating robust process windows for key manufacturing modules is critical – but time-consuming. Traditional experimental learning cycles can extend project timelines significantly. This presentation showcases an innovative approach that combines TCAD simulation data with JMP’s cutting-edge Bayesian Optimization plat...

Matteo Patelmo and others

Bayesian Optimization for Formulations Involving Complex Constraints with JMP 19 (2026-EU-30MP-2816) The production of many products involves mixing or blending multiple ingredients. Finding optimal formulations for these products can be challenging, expensive, and time-consuming, especially if the formulation is subject to complex constraints. The ability to innovate new high-quality products quickly is becoming increasingly more important as technologies advance and competition increas...

Christopher Gotwalt and others

JMP 19の新機能このプレゼンテーションでは、JMPのチーフデータサイエンティストであるChris GotwaltよりJMP 19の新機能についてご紹介します。特に今回の新リリースの目玉である、ベイズ最適化について解説します。これは、産業界における製品やプロセスの最適化のための「アクティブラーニング」フレームワークであり、製品開発プロジェクトの時間とリソースを劇的に削減します。また、以下の新機能も取り上げる予定です。プロファイラーコントロールパネルの刷新: モデルの最適化設定やカスタマイズがより簡単にできるようになります。因果関係の分析（傾向スコアマッチング）: 医療やライフサイエンス分野で重要な、観察データにおける因果関係の解明に役立ちます。 FDEにおけるピークモデリングとベースライン補正の手法

Christopher Gotwalt JMP

開会のご挨拶／基調講演：イノベーションの拡大：エンジニアリング・ワークフローへのデータサイエンス統合 10:00～10:15：開会のご挨拶10:15～11:15：基調講演今日のエンジニアリングにおける課題は、もはや局所的な解決策だけでは不十分です。データサイエンスの手法をデータ分析のワークフローに組み込むための、拡張性が高く柔軟なツールが求められています。JMPの製品群は、統計解析、プロセス最適化、データ視覚化のための強力なプラットフォームを提供し、エンジニアが日々の問題解決を超えて活躍できる環境を創造します。このセッションでは、複雑で大規模な問題への取り組みに焦点を当て、JMPがどのようにエンジニアリング・データサイエンスを支援するかを深掘りします。あわせて、データアクセス、プロセススクリーニング、環境モニタリング、グループ別分析、モデル・応答スクリーニング、そしてJMP Liveとの統合といったツールに焦点を当て、JMPが多様なニーズにどのように対応するかを解説します。具体的な事例やデモ...

Skill level: beginner

Jules Parris and others

Understanding Bioprocess Complexity: Advanced Analytical Profiling and JMP (2025-US-30MP-2597) The biopharmaceutical industry has generated many valuable products. Yet if the analytical tools used are difficult to operate or don't work in concert, practioners can struggle to understand the complex systems they employ to achieve those Eureka moments. We demonstrate a real-world example of the powerful combination of routine PAT (process analytical testing) using chemical analytics performed b...

Patrick Boyce and others

Lies, More Lies, or Just Statistics? JMP FDE Will Be the Judge (2025-US-30MP-2539) Polygraph examinations play a very important role in such situations as event investigations and employment screenings. Polygraph examinations monitor psychological reactions to determine if an individual is being deceptive or telling the truth. Being able to determine if an individual is being deceptive with a non-biased approach is of utmost importance. Many of the scoring techniques used to...

Megan Pennington and others

Models, Bootstraps, and Monte Carlo...Oh My! Designing With Small Samples (2025-US-30MP-2503) In the development of new products or processes, sample sizes are often small. Even so, we want to make educated decisions about the performance of the new product or process. This presentation demonstrates the use of bootstrapping, modeling, and Monte Carlo simulation to understand how a process might perform, even with small samples. Because these tools are readily available i...

Dale Human ray Generation

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