HTTP Interface and External Systems for Lead Optimization

Data Characteristics in This Category

Lead optimization data primarily originates from high-throughput screening (HTS) results, computational chemistry simulations, in vitro ADME (Absorption, Distribution, Metabolism, Excretion) predictions, and preliminary toxicology assessments. This data exists in structured and semi-structured formats. Examples include compound SMILES strings, IC50/EC50 values, logP/logD values, solubility, and CYP enzyme inhibition activity. Data update frequency is relatively high, especially in laboratory environments with frequent compound synthesis and testing. Documentation typically includes standardized experimental reports, Structure-Activity Relationship (SAR) tables, and batch analysis data. Field names and units are industry-standard, but specific naming conventions may vary depending on the Laboratory Information Management System (LIMS) or Electronic Lab Notebook (ELN).

Constraints Imposed by These Characteristics on "HTTP Interface and External Systems"

The high-throughput and multi-source nature of lead optimization data requires HTTP interfaces to have efficient data aggregation and processing capabilities. Frequent data updates mean the interface needs to support real-time or near real-time incremental synchronization, avoiding the performance overhead of full refreshes. The mixture of structured and semi-structured data challenges the robustness of data parsing and standardization, particularly for non-textual information like compound structures. Variations in field and unit standardization require flexible mapping or conversion within interface configurations to ensure data consistency. Additionally, due to sensitive research and development data, interface authentication and authorization mechanisms must be strict. Error handling mechanisms must precisely report specific reasons for data validation or processing failures, such as compound structure parsing errors or activity values outside the expected range.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`maxContext`	`2000 characters`	Ensures typical compound structure information, activity data, and descriptions are fully accommodated.
`API_TIMEOUT_SECONDS`	`60 seconds`	Balances high-throughput batch data submission with network latency to avoid frequent timeouts.
`auth_header_name`	`X-API-Key`	Common industry practice, providing a flexible way to pass authentication tokens.
`rate_limit_per_minute`	`120 times`	Balances data update frequency with external system capacity to prevent overload.
`response_schema`	`{ "status": "success", "data": [...] }`	Defines a clear response structure for easy parsing of results and consistent error codes and data payloads.
`error_field_path`	`$.error.message`	Precisely specifies the path to error messages for quick problem identification.

Three Common Mistakes

Symptom: API returns a 401 Unauthorized error, even when an API Key is configured. Reason: The auth_header_name configuration does not match the authentication header name required by the external system, or the auth_value is incorrectly populated or expired.
Symptom: The interface returns Model response empty or data parsing exceptions. Reason: The data structure returned by the external system does not match the response_schema configuration, or the JSON format is incorrect, preventing FastGPT from correctly extracting the required fields.
Symptom: Some compound data is not synchronized or is incompletely synchronized. Reason: The compound SMILES string returned by the external system contains special characters that are not encoded, or the activity unit is inconsistent with expectations, leading to data validation failure and filtering.

How to Verify Configuration

Use FastGPT's interface testing feature to perform an end-to-end test with typical lead compound data. Verify that data is correctly submitted and received by the external system.
Check FastGPT's backend logs. Confirm there are no API_TIMEOUT_SECONDS related timeout records and that data synchronization frequency meets expectations.
Query the synchronized compound data in the external system. Verify that key fields such as SMILES strings, activity values, and ADME parameters match the source data, paying close attention to units and data types.

Note: The values provided are common starting points and should be measured against specific samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.