Announcement • Jul 15
Prf Technologies Expands Deepsolar Predict Platform with Battery-To-Revenue Intelligence PRF Technologies Ltd. announced the expansion of DeepSolar Predict, the Company’s AI-driven renewable energy revenue optimization platform, with Battery-to-Revenue Intelligence, a new capability designed to extend the platform’s optimization workflows to battery energy storage assets. Battery-to-Revenue Intelligence is designed to help renewable energy operators move beyond battery monitoring by connecting storage availability, operational constraints and market conditions into decision-support workflows for revenue optimization. The capability is intended to support operators as they evaluate when to store, dispatch or preserve battery capacity based on market opportunities, production forecasts and changing grid conditions. DeepSolar Predict is being developed as an end-to-end decision-support solution that connects the full renewable energy value chain — from weather intelligence and production forecasting to storage optimization, market participation and revenue-focused recommendations. By bringing these capabilities together in a single platform, PRF aims to help operators move from fragmented operational tools toward a unified environment for commercial decision-making. The new capability is designed to evaluate battery operating conditions, including state of charge, availability, charging and discharging behavior, operational readiness and other constraints, and to incorporate these insights into the platform’s revenue optimization workflows. As part of its product roadmap, PRF also plans to deliver a “What-if Battery Scenario” capability designed to help asset owners evaluate the potential revenue impact of adding or operating battery storage within a renewable energy portfolio. Based on ongoing discussions with prospective customers, the Company believes scenario-based storage analysis is increasingly relevant for renewable energy operators evaluating how batteries may contribute to improved market participation, reduced exposure and stronger revenue performance. PRF believes Battery-to-Revenue Intelligence represents another step in the evolution of DeepSolar Predict from asset analytics and forecasting into AI-driven revenue optimization. The Company also expects these capabilities to serve as a core component of GridFeed, PRF’s planned commercial platform for renewable energy trading and market participation, built on the DeepSolar Predict AI engine, which the Company intends to introduce more fully in the coming weeks. DeepSolar Predict is the Company’s AI-driven revenue optimization solution for renewable energy assets and energy market participants. The solution combines weather intelligence, production forecasting, market intelligence and optimization workflows designed to support decision-making across energy markets. By transforming operational and market data into actionable recommendations, the platform aims to help renewable energy operators improve planning, support market participation and maximize revenue. Announcement • Jul 09
PRF Technologies DeepSolar Business Unit Completes Initial Validation Phase For DeepSolar Predict AI-Driven Revenue Optimization Platform PRF Technologies DeepSolar business unit has completed an initial validation phase for DeepSolar Predict, the Company’s next generation AI-driven revenue optimization platform, marking another step toward the solution’s planned commercial launch. The validation applied real-world historical weather data, renewable energy production records and market data - including utility-scale datasets and market conditions representative of European energy markets - to evaluate the platform’s optimization recommendations and decision-support workflows across day-ahead and intraday scenarios under a range of operating conditions. DeepSolar Predict combines weather intelligence, production forecasting and market analytics to support decision-making across day-ahead and intraday energy markets. The validation phase builds on platform milestones announced earlier this year, including DeepSolar’s participation in the NVIDIA Connect program and the Company’s patent application covering plant-level micro-climate modeling. DeepSolar Predict is the Company’s AI-driven revenue optimization solution for renewable energy assets and energy market participants. The solution combines weather intelligence, production forecasting, market intelligence and optimization workflows designed to support decision-making across energy markets. By transforming operational and market data into actionable recommendations, the platform aims to help renewable energy operators improve planning, support market participation and maximize revenue. Announcement • Jun 26
PRF Technologies Reports Expanded Preclinical Results For PRF-110 In Head-To-Head Comparison With Approved Benchmark PRF Technologies announced expanded results from its previously reported preclinical study directly comparing its lead product candidate, PRF-110, to ZYNRELEF (bupivacaine and meloxicam extended-release solution), an approved extended-release product used as a benchmark in the study. The expanded results characterize the pharmacokinetic (PK) and tissue-distribution properties of PRF-110 alongside the analgesic efficacy data previously announced. PRF-110 is a proprietary, oil-based, viscous, clear extended-release formulation of ropivacaine designed to be deposited directly into the surgical wound bed prior to closure. The product candidate is being developed to provide prolonged local analgesia following surgery through a single administration at the surgical site, with the goal of reducing the use of opioids for post-surgical pain. The study was conducted in a validated porcine post-operative pain model, using von Frey methodology, to assess both analgesic efficacy and PK properties of the two extended-release formulations. PRF-110 and ZYNRELEF demonstrated similar reductions in mechanical sensitivity, as measured by the von Frey test, indicating comparable pain-relief performance. PRF-110 exhibited a slower absorption rate relative to ZYNRELEF, suggesting a more gradual release of ropivacaine at the site of administration. PRF-110 showed increased retention in local tissue along with higher local tissue exposure (Cmax), supporting prolonged availability of the active compound at the target site. Both formulations demonstrated sustained systemic and local drug levels, reinforcing their potential as long-acting analgesic solutions. PRF plans to continue advancing PRF-110 through additional studies to further validate its safety, efficacy and clinical utility across broader surgical settings. PRF-110 is a proprietary, oil-based, viscous, clear extended-release solution based on the local anesthetic ropivacaine and is being developed for the post-operative pain relief market. PRF-110 is designed to be deposited directly into the surgical wound bed prior to closure to provide localized and extended post-operative analgesia. The formulation is designed to remain in place at the surgical site, spread over and adhere to the wound surface, resist rapid clearance, and provide sustained local release of ropivacaine. PRF-110 is being developed to provide prolonged post-operative pain relief following a single administration, with the goal of reducing the need for repeated dosing and potentially reducing reliance on opioids after surgery. 
