Accurate K _d determination is crucial for drug discovery and diagnostics. Accuracy confidence intervals (ACI)-ITC, a browser-based tool, calculates ACI for isothermal titration calorimetry (ITC)-derived parameters, considering systematic errors in concentration and heat measurements. By offering probabilistic ranges for true K _d, ΔH°, and stoichiometry value n, ACI-ITC enhances experimental reliability, guiding better decisions, streamlining cross-platform accuracy assessments, and improving trust in ITC-based findings.

Accurate determination of equilibrium dissociation constants (K _d) is essential for decision-making in drug discovery and diagnostics development. Isothermal titration calorimetry (ITC), which requires no reactant labeling or immobilization, is commonly used to validate K _d values from high-throughput screens. Yet, like other methods, ITC results can be skewed by systematic errors in reactant concentrations, a fact that is often overlooked, potentially leading to misinformed decisions. To address this, accuracy confidence intervals (ACI)-ITC is developed, a browser-based tool that calculates ACI for ITC-derived parameters, offering probabilistic ranges for the true values of K _d, enthalpy change (ΔH°), and binding stoichiometry (n). Unlike traditional confidence intervals that consider only random errors, ACI-ITC explicitly accounts for systematic errors, providing a more accurate framework to assess experimental reliability. Alongside a user-friendly interface, it offers detailed guidance for determining uncertainties in concentrations and heat, which are critical inputs for assessing measurement accuracy. The tool's browser-based accessibility (https://aci.sci.yorku.ca) eliminates the need for specialized installation, enabling cross-platform compatibility and streamlining accuracy assessments. By highlighting the importance of systematic errors and providing a structured approach for their evaluation, ACI-ITC supports more robust conclusions, fosters better-informed decisions based on ITC measurements, and enhances the reliability of research findings.