Drug Discovery Support System StarDrop - Introduction to the High-Performance Metabolism Prediction Module

Achieving improvements in the speed, efficiency, and productivity of the drug discovery process! We quickly provide optimally balanced compounds.

By quickly extracting diverse and excellent compounds, StarDrop operates while evaluating complex data, dramatically reducing the time required for effective lead compound exploration. In evaluating this data, it provides confidence and intuitive clarity for decision-making, guiding and validating the direction of research and which compounds to prioritize. This interactive tool enables you to efficiently open pathways to enhance your chosen chemical properties. 〇 Advantages of StarDrop - Development of more effective drugs By highlighting excellent chemical properties, it leads you to target areas with the greatest potential for multifaceted optimization and success in your research. - Confident decision-making It assists in managing uncertain data specific to drug discovery that arises from experimental variability and predictive errors. - Speeding up compound selection It significantly reduces the time needed to navigate the maze of possibilities and identify excellent lead compounds and candidate drugs. - More results from your research It helps you get the best from all your resources, delivering true value.

• Other research software
• Data Mining
• Bioinformatics

Improve the speed, efficiency, and productivity of drug discovery. Quickly find the optimal compounds.

In the pharmaceutical industry, the drug discovery process is a complex one that requires significant time and cost. Particularly, finding the optimal compound is a crucial challenge that determines the success of new drug development. StarDrop addresses this challenge by quickly extracting a diverse range of excellent compounds, dramatically reducing the time required for drug discovery. It evaluates complex data and supports the determination of research direction and compound prioritization. As a result, researchers can make decisions more efficiently and with greater confidence. 【Use Cases】 - Exploration of lead compounds - Selection of candidate drugs - Optimization of compound properties 【Effects of Implementation】 - Reduction of drug discovery time - Decrease in research and development costs - Development of more effective pharmaceuticals

• Other research software
• Data Mining
• Bioinformatics

We support the design of compounds to enhance food safety.

In the food science industry, the development of new products and quality design is a complex process involving multifaceted evaluations such as taste, aroma, texture, nutritional components, and safety. The decision support platform StarDrop contributes to the efficiency of food R&D by evaluating and predicting the chemical properties of food ingredients and functional materials based on data, quickly identifying optimal blends and formulations. 【Main Use Cases】 - QSAR Property Prediction: Predicting the in vivo behavior (such as absorption and metabolism) and physical properties of specific components before synthesis and formulation. - Toxicity and Safety Prediction: Screening the toxicity risks (such as skin sensitization and mutagenicity) of raw materials and additives at an early stage. - Auto-Modeller: Building unique quality prediction models from the company's experimental data (such as sensory evaluation and shelf life). 【Implementation Effects】 By simultaneously optimizing blends that balance taste, safety, and health functions, the number of prototypes is minimized, achieving a "dramatic reduction in development time" and "reduction in prototype costs." This accelerates the market introduction of advanced health foods and new materials that meet consumer needs.

• Other research software
• Data Mining
• Bioinformatics

Achieving improvements in the speed, efficiency, and productivity of the drug discovery process!

In the cosmetics industry, the development of skincare and makeup products is a complex process that requires the simultaneous optimization of various characteristics such as skin permeability, safety (low irritation), stability of active ingredients, and user experience. The decision support platform StarDrop contributes to the efficiency of cosmetics R&D by efficiently evaluating and predicting the chemical properties of beauty ingredients and raw compounds, allowing for the rapid identification of optimal formulations. 【Main Use Cases】 - Skin Permeability and ADME Prediction: Predicting whether active ingredients can pass through the skin barrier and reach the targeted layers (skin permeability) before synthesis and formulation. - Toxicity and Low Irritation Prediction: Screening the skin sensitization (allergic reactions) and eye irritation risks of raw materials and additives at an early stage. - Auto-Modeller: Building unique product evaluation prediction models from the company's experimental data (sensory evaluation, texture, stability tests, etc.). 【Implementation Effects】 By digitally narrowing down to a "golden formulation" that meets high safety, proven efficacy, and excellent user experience, we achieve a "dramatic reduction in development time" and "reduction in prototype costs." This accelerates the market launch of clean beauty and personalized cosmetics.

• Other research software
• Data Mining
• Bioinformatics

Evaluating drug efficacy, safety, pharmacokinetics, and physical properties comprehensively from the early stages of the drug discovery process is essential for efficient pharmaceutical development. To support these evaluations comprehensively, the drug discovery support software StarDrop offers various modules. In this presentation, we will introduce an overview of the functions included in the metabolism prediction module, the Metabolism module, its theoretical background, and how it contributes to solving various challenges related to drug metabolism.

We will be exhibiting at the JASIS exhibition held at Makuhari Messe International Exhibition Hall this year as well. [Exhibited Products] ■ High-resolution ICP optical emission spectrometer ■ Continuous light source atomic absorption spectrometer ■ TOC analyzer ■ Microwave sample digestion system [Exhibitor Seminars (New Technology Presentations)] ■ September 3 (Wed) 12:00–12:30 [Atomic Absorption] Venue: Makuhari Messe Conference Hall, Room 101 Surpassing the limits of atomic absorption analysis! A xenon continuous light source atomic absorption spectrometer that achieves efficient measurements like ICP-OES with easy operation. ■ September 4 (Thu) 15:00–15:30 [ICP-OES] Venue: TKP (formerly APA) Venue, Room No. 7 How far can we go? High-sensitivity analysis using a high-resolution ICP optical emission spectrometer equipped with an Echelle double monochromator and CCD detector. ■ September 5 (Fri) 15:00–15:30 [Trace Nitrogen, Sulfur, Chlorine] Venue: TKP (formerly APA) Venue, Room No. 1 Fully compliant with petrochemical JIS standards! A multifunctional nitrogen, sulfur, and chlorine analyzer that condenses solutions for routine analysis and research and development challenges into one device.

[Speaker] Representative Lawyer Hiroshi Noma, Hatsuki Law Office [Key Lecture Content] Climate change has become an urgent global issue, and decarbonization is a critical challenge in the energy/power sector. At the same time, the demand for electricity in data centers is rapidly increasing due to the proliferation of generative AI and cloud services. This seminar will provide a clear explanation of the latest trends in power generation development and electricity procurement in the decarbonization era, using green data centers that utilize corporate PPAs and non-fossil certificates as a subject. It will cover related policies and systems, such as the establishment of renewable energy as a primary power source and watt-bit collaboration, from the perspectives of both power generation companies and consumers. [Lecture Items] 1. Trends in decarbonization policies 2. The flow of new electricity demand - Data centers - 3. Latest trends in renewable energy power generation development 4. Procurement methods for renewable energy power from the consumer's perspective 5. Q&A / Business card exchange

[Speaker] Mr. Lee Qiangfu, Chief Analyst, Technical Research Department, Fourin Inc. [Lecture Topics] 1. SDV → AIDV: The status of AI adoption by major automobile manufacturers 2. Competition in AI + ADAS / Autonomous Driving 3. Changes in the nature of automobiles and profitability models associated with the incorporation of AI 4. Future prospects of AIDV competition 5. Q&A / Business card exchange

Did you know that the success or failure of an ERP upgrade project is actually determined by the integration plan with surrounding systems? Many companies are facing unexpected troubles as a result of relying solely on their ERP vendors. In this seminar, an SE who has been involved in numerous ERP upgrade projects will provide a detailed explanation of practical integration plans that lead to successful ERP upgrades. This is essential content for information systems personnel preparing for an ERP upgrade. You will take home specific know-how that can significantly reduce project risks through advance measures. <Recommended for> - Those who are preparing for an ERP upgrade in 1 to 3 years and are gathering information on what to prepare. - Those who want to understand the project risks of an ERP upgrade in advance. - Those who are considering how to efficiently succeed in an ERP upgrade within budget and schedule constraints.