DP Technology Launches AI Drug Chemistry Assistant PharMaster, Cutting Target Evaluation Time by 80%
DP Technology
Simulation R&D Platform Developer
November 15, 2025, in Shenzhen, ChinaAt the Xili Lake Forum, DP Technology officially releasedPharMaster——An AI research and development partner that truly understands the working patterns and decision-making approaches of medicinal chemists. PharMaster starts with the core tasks of medicinal chemists during the target initiation phase, systematically integrating three major information dimensions: biological mechanisms, market intelligence, and patent analysis, significantly reducing the time required for information integration and data processing, allowing researchers to focus on critical professional judgment tasks.The average3 Week'sTraditionalTarget research cycle compressed to3 DayCompleted。
Dr. Zheng Xing, Chief Engineer of Biomedical R&D at DP Technology,
PharMaster Released at Xili Lake Forum in Shenzhen
Target Initiation: Decision Item
Key Decision on the Direction
In the research and development of innovative drugs, target project initiation is widely considered to be the decision-making node with the highest value, greatest risk, and most far-reaching impact."10% of the input determines 90% of the value" has become an industry consensus.。Whether a certain target has drug development potential, and whether the potential output can cover hundreds of millions or even billions of R&D investment, is a professional judgment that pharmaceutical chemists must make.
However, forming a reliable conclusion for project initiation is not an easy task. Medicinal chemists needEvaluate market size, competitive landscape, biological mechanisms, developability, safety, and other professional dimensions simultaneously.，And these key pieces of information are often scattered across a vast amount of literature, patents, databases, news articles, and industry reports. Even experienced researchers typically require a significant amount of time to complete a full round of target research from scratch.Exactly three weeksOnly then can a relatively confident judgment be formed.
It is precisely this complexity and challenge that makeTargetProject Establishment Becomes InspectionAI The core scenario of Agent's professional adaptability in the field of drug research and development is when Agent can demonstrate exceptional capabilities in this critical环节, it signifies that it has truly mastered the professional essence of drug research and development.
Traditional Research and Existing AI Tools:
Why is it still difficult to truly reduce the burden?
In real work, the part where medicinal chemists spend the most time is often not the judgment itself, but the "preparation work" before the judgment:
Biological Mechanism Research：It requires extracting key conclusions from a large number of literature and cross-validating them, usually taking 5–8 person-days.
Market Information Collection：It is necessary to screen the pipeline layout and competitive products from databases and the Internet, usually requiring 3–5 person-days.
Patent Analysis：Manually drawing molecular structures, comparing activities, and constructing SAR typically requires 8–12 person-days.
In recent years, general-purpose AI, while able to assist in information retrieval, still has four significant bottlenecks:
1. The quality of information sources varies, and the credibility of key evidence is difficult to guarantee;
2. Lack of a professional medicinal chemistry knowledge system, unable to cover comprehensive analysis for target project initiation;
3. The output format is mainly stacked text, with lengthy expressions and insufficient structuring;
4. The content is not rigorous and timely enough, and the results generated at different times vary greatly.
As a result, researchers still need to invest a significant amount of time in reading, screening, and re-evaluating, with limited overall efficiency improvement.
PharMaster: A Truly
"AI Assistant for 'Pharmaceutical Chemists'"
The design goal of PharMaster is not to "help users retrieve information," but to truly empower medicinal chemists.Save more time, make better judgmentsWe summarize the "pharmaceutically knowledgeable chemist" into three key criteria:
1. Reliable Source: Based on High-Quality Evidence
PharMaster relies on high-quality literature, patents, and domain databases that are widely trusted by pharmaceutical chemists as its core data sources. For instance, in bio-mechanism analysis, the system prioritizes references fromNature、Nature Medicine、J. Med. Chem. WaitMore than 50Portion Pharm ChemistLong-termTrusted Core JournalsHigh-quality evidence to ensure conclusions are based on reliable data sources.
2. Comprehensive Information: CoverageTargetProfessional Dimensions to Consider for Project Initiation
PharMaster addresses core issues such as biological mechanisms, market landscape, developability, and safety by constructing an information framework tailored to the research methods of medicinal chemists. This framework includes key modules such as structural domains, signaling pathways, expression profiles, disease associations, research tools, and potential safety concerns, among others.Build Multi-Agent for Each Niche FieldSystem ImplementationCollaborative Extraction and Cross-Validation, ensuring the timeliness and rigor of the content.
3. Report readability: Structured presentation, key points highlighted
PharMaster Intelligent Generation Research ReportPresent key evidence, charts, and conclusions in a clear structure, avoiding堆积long texts., allowing researchers to focus on core issues more quickly.
Three Major System Capabilities: How
Achieving "From Three Weeks to Three Days"
1. High QualityBiomechanism Analysis: FromMulti-source High ReliabilityEvidence BuildingHigh QualityMechanism Spectrum
PharMaster integrates multi-source and highly reliable scientific data, intelligently constructing coverage across structural domains,High-quality structured mechanism maps of pathways, expression profiles, disease associations, and potential safety, combined with visual charts and evidence annotations, make mechanism inference more aligned with the professional decision-making approach of medicinal chemists.
2. High CoverageMarket InformationIntegration: Quickly Identify Strategic Directions in Complex Data
The system integrates global public pipeline data, statistics on R&D stages, drug types, and company layouts, and visually presents the distribution of clinical stages, mechanism hotspots, and unmet clinical needs. Researchers can quickly grasp the position of targets in the industry chain without manually comparing heterogeneous information.
3. High PrecisionPatentIntelligentAnalysis: Replacing a large amount of repetitive manual labor with automation technology
Patent analysis is one of the most time-consuming and error-prone tasks for medicinal chemists. In this step, PharMaster, based on DP Technology's self-developed high-precision analysis framework, implements a closed-loop system from "model pre-labeling → manual correction → expert review → model improvement," with a structural accuracy rate exceeding94%, with an accuracy rate of property data exceeding99%。
DP Technology has analyzed more than400,000 Drug Molecule Patents, building a coverage of 2,000+ Target, 6 million compounds and 13 million activity dataThe "Thousand-Target, Ten-Thousand-Drug" database. PharMaster can automatically extract structures, align activities, and generate SAR views, automating processes that originally required extensive manual drawing and organization, allowing researchers to focus their time on areas that truly require professional judgment.
Shorten 3 Weeks to 3 Days: Accelerate Drug
Experts Focus on Core Analysis and Decision-Making
The changes brought by PharMaster are not just "faster research," butFundamental Remodeling of Temporal Structure。
In the past target research, over 80% of the time was allocated to repetitive processes such as literature dissection, information collection, structure drawing, and data cleaning. However, PharMaster significantly compresses these time-consuming steps through structured mechanism mapping, visualized market landscapes, and automated patent analysis, allowing researchers to focus their time on the truly core tasks: analyzing evidence, identifying risks, assessing feasibility, and driving decision-making.
From 3 weeks to 3 days, it's not just an efficiency improvement, but also a shift in professional approach.
FromTargetProject InitiationStart, Reshaping the R&D Process of Innovative Drugs
Target立项 is the entry point for PharMaster, but not the endpoint. Currently, PharMaster has been deeply integrated with more than 70 computational tools on the Hermite platform, enabling direct access through natural language interaction; at the same time, relying on the "千靶万药" database, it is progressively covering multiple core R&D stages, including hit identification, lead optimization, and drug-likeness analysis.
In the future, PharMaster will become the AI partner that researchers can rely on at any time throughout the drug research and development cycle.
PharMaster is now available for trial, looking forward to becoming your AI partner.
PharMaster is now officially open for trial use by enterprises and research teams. We look forward to PharMaster's capabilities in providing high-quality evidence, intelligent analysis, and structured results, which will support your target validation, molecular design, and project advancement, allowing you to devote more valuable time to the most critical decision-making processes.
Welcome to scan the code to apply for a trial and experience how AI Agent is reshaping the drug R&D process.
About DP Technology
Relying on deep cultivation in the field of interdisciplinary research, DP Technology has built the "Deep Potential·Universe" AI for Science large model system, further addressing key issues in scientific research and industrial development. This effort transitions research methods across numerous disciplines from the "experimental trial-and-error/computational" era into the "pre-trained model era," establishing an "innovation-to-application" pipeline and open ecosystem for AI for Science. It constructs microscale industrial infrastructure based on AI for Science, empowering "thousands of industries," and developing a new generation of R&D systems for the most fundamental areas of human economic development: biomedicine, energy, materials, and information science and engineering.
DP Technology is a national high-tech enterprise and a national specialized, refined, novel "little giant" enterprise, with research and development centers located in cities such as Beijing, Shanghai, and Shenzhen. The scientific research team is led by an academician of the Chinese Academy of Sciences, gathering over a hundred outstanding young scientists and engineers from various fields including mathematics, physics, chemistry, biology, materials, and computer science. Among them, the proportion of PhDs and postdoctoral researchers exceeds 35%. Core members have received the 2020 Gordon Bell Prize, the highest award in the global high-performance computing field, and their related work has been selected as one of China's top ten scientific advances in 2020 and one of the ten major technological breakthroughs in the global AI field.
