Illinois R&D Tax Credit Filing Instructions

To claim the Research and Development (R&D) tax credit in Illinois, businesses must engage in qualified research activities as defined under Section 41 of the Internal Revenue Code, specifically those performed within the state. The Illinois R&D credit is a nonrefundable credit equal to 6.5% of the qualifying expenditures that exceed a base amount, which is the average of the qualifying research expenditures (QREs) for the three preceding taxable years. These qualifying expenditures typically include wages for qualified services, the cost of supplies, and rental or lease costs of computers, as well as contract research expenses.

Businesses must file Illinois Schedule 1299-D, Income Tax Credits (for corporations and fiduciaries), or Schedule 1299-A, Tax Subtractions and Credits for Partnerships and S Corporations, depending on their entity type. This schedule must be attached to their appropriate Illinois tax return, such as Form IL-1120 (for corporations), Form IL-1041 (for fiduciaries), or Form IL-990-T (for unrelated business income tax). Unused credits can generally be carried forward for up to five years. It’s essential for businesses to maintain thorough documentation of their R&D activities and expenses to support their claim in the event of an audit.

Illinois Patent of the Year – 2024/2025

Mental Health Technologies Inc. has been awarded the 2024/2025 Patent of the Year for its innovative approach to mental health treatment optimization. Their invention, detailed in U.S. Patent No. 11894146, titled ‘Systems and methods for allocating resources in mental health treatment’, introduces a data-driven method to personalize and enhance mental health care delivery.

This patented system leverages advanced algorithms to analyze individual patient profiles, incorporating data such as symptoms, medical history, and treatment responses. By computing a personalized wellness score and tracking its progression over time, the system assesses treatment efficacy on an individual level. It then compares these metrics across a broader patient population with similar conditions to identify patterns and correlations.

Utilizing this comparative analysis, the system can recommend tailored treatment regimens, optimizing resource allocation to improve patient outcomes. Factors influencing treatment success, both fixed and variable, are considered to adjust strategies dynamically. This approach not only aims to enhance the effectiveness of mental health interventions but also seeks to allocate resources more efficiently, ensuring that patients receive the most appropriate care based on their unique needs.

By integrating comprehensive data analysis into the treatment planning process, Mental Health Technologies Inc.’s innovation represents a significant advancement in personalized mental health care, with the potential to improve both patient experiences and clinical outcomes.