The All-New PromptBio Platform is an agentic AI platform for life sciences, released by PromptBio Inc. on June 9, 2026. It aims to transform a researcher's scientifically-expressed intent, articulated in natural language, into an executable bioinformatics analysis workflow. When a user inputs a research question or hypothesis, it orchestrates multiple specialized agents tailored for literature review, multi-omics, proteomics, and drug discovery, connecting them within a single environment, from the selection of relevant data to the execution of analysis pipelines, visualization, and the generation of reproducible reports. Similar to how GPT transforms natural language requests into sentence-level results, PromptBio is more akin to a platform that translates scientific questions into a research execution plan consisting of combined data and analysis steps. In traditional bioinformatics analysis, researchers must manually connect analysis steps by navigating between paper search services, public data repositories, statistical packages, visualization tools, and report writing environments. In this process, data format conversion, setting input conditions for each tool, transferring intermediate results, and managing execution logs often become bottlenecks. The key differentiator of PromptBio is that it goes beyond simply providing individual analysis functions; it orchestrates multiple specialized agents and analysis steps into a single, continuous flow centered around scientific intent. In other words, instead of having researchers directly operate various instruments, it aims to function as an orchestrator, receiving a "score" in the form of a research question and conducting the specialized agents. Researchers can utilize this in a workflow where they inquire about candidate genes related to a specific disease or phenotype, connect literature-based evidence gathering with multi-omics data analysis, and then organize the results into a visualized report. In protein research, it can be used to investigate existing research on a target and construct analysis steps from a proteomics perspective to narrow down potential candidates for subsequent experiments. In the early stages of drug development, it can be used to connect a disease hypothesis, target-related literature, and available biological data into a single analysis flow to review the prioritization of candidate targets. However, the supported databases, individual analysis tools, model names, parameter exposure ranges, and quantitative performance could not be confirmed based solely on the provided information, so official document verification is necessary before actual research application. The reproducible report generation feature is particularly meaningful for research teams that aim to track not only the analysis results but also the data selection and pipeline execution processes. However, since it is a proprietary service, the storage location of uploaded data, retention period, whether the data is used for model training, access control, ownership of the results, and conditions for processing regulated data must be confirmed separately. The workflows and results presented by the platform should be treated as hypothesis generation and analysis aids, and researchers should independently review the raw data, statistical methods, cited literature, and execution logs before using them for clinical judgment or experimental conclusions.

The All-New PromptBio Platform is an agentic AI platform for life sciences, unveiled by PromptBio Inc. on June 9, 2026. It aims to translate researchers' scientifically-expressed intentions, expressed in natural language, into executable bioinformatics analysis workflows. When a user inputs a research question or hypothesis, it orchestrates multiple specialized agents tailored for literature review, multi-omics, protein science, and drug discovery, connecting everything from the selection of relevant data to the execution of analysis pipelines, visualization, and the generation of reproducible reports, all within a single environment. GPT handles the natural language.

Explore disease-related candidate genes: A researcher inputs a natural language hypothesis about a disease or phenotype, and connects a literature search agent with a multi-omics analysis workflow to generate a reproducible report summarizing candidate genes and supporting evidence. Supported datasets and statistical parameters require verification in the official documentation.