CureHunter Discovery Engine: Transforms Medline into Systems Biology Machine for real time evidence based medicine and new cure discovery

The CureHunter Systems Biology Machine was designed to meet the NIH "Bench to Bedside Program" goal for rapid translation of pure research into an Evidence-Based Medicine System usable in real time at the point of clinical care, and the FDA "Critical Path Initiative" goal for rapid discovery of new cures using built in CA-DDD: Computer Aided Drug Discovery and Development models.  Operationally, CureHunter is a web browser-accessible artificial intelligence system designed to autonomously machine read and data mine the entire National Library of Medicine Medline archive 1893 to the current hour of electronically updated articles, automatically extract the key Clinical Evidence for drug effectiveness against a target disease, and compute the optimal treatment medications based on the sum of the Outcomes Evidence with: 1 Mouse Click / 10 Seconds of Real Time. CureHunter’s key output is an evidence-based meta-analytic "Machine 2ndOpinion" consult that proves especially valuable when first and second line drugs are proving ineffective, unsafe, or intolerable--often estimated to be 35% of all prescriptions. Thus if clinic reception nurses were to make a CureHunter drug evidence check as SOP as a BP or temp, it is straight forward to predict that the US health care system could save $30+ billion per year by: 1) minimizing the use of drugs that drive expensive ER visits at the current rate of 400 per thousand population costing on average $2,500 each and 2) minimizing the 2nd largest cost, recurring clinical visits to ask the physician to change out those drugs that are ineffective, unsafe, adverse, intolerable or fraught with hazard and liability. CureHunter’s "Machine 2nd Opinion" can and should, of course, be challenged; but CureHunter routinely passes the Turing Test; and it is well to remember that the human experts themselves may be wrong, as CureHunter has read all of Medline and they have not. In fact, routine disagreement among experts is a common feature of medical life and another reason why an unbiased, extremely well read AI arbiter, immune to peer institutional pressure and deregulated drug advertising may be the physician’s best counselor when faced with complex drug decisions? User System Access and Interface: All of CureHunter’s primary web-accessible outputs are provided free and pro bono for 3 user groups with Net connected PCs, Tablets or Cell Phones running IE 8 or 9 (in compatibility view) Firefox, Opera, Safari, Chrome or Android 3.0 with Adobe Flash Enabled (Motorola, Samsung, Blackberry, et al). Large screens, however, are recommended: . Patients (no registration required) activated from home page . Physicians or Scientists (lite PRO version requires registration but no fee) activated by logging in after registering and clicking Research on header bar . Pharma Researchers same as above All users of the public NLM Challenge version described here need only enter 1 word into CureHunter’s main home page or Research query field if using the registered version: The NAME of the disease for which a cure is sought. Upper left field:  www.curehunter.com Note well: CureHunter is NOT a "search engine" or general bibliographic index. Do not enter author names, article titles, subject keywords, Boolean operators, etc.; all queries are hardwired and optimized in CureHunter to scientifically sample and data mine outcome-specific evidence that can be quantified and cross-tabulated for meta-analysis and new cure discovery. Thus many articles that may offer general commentary on a health issue are filtered out for lack of scientific utility in the CureHunter model. Patient Outputs appear automatically on the 2ndpage after the Disease NAME entry: . List of drugs rank ordered by evidence only of successful treatment outcomes derived directly from peer-reviewed data completely unaided or biased by human editing and drug advertising . RSS feeds of up-to-the-minute disease-specific new research including electronic pre-press: Can auto feed user’s email box with hopeful new findings for those facing chronic, incurable, or terminal illnesses and automatically keep physicians up to date on latest treatments and research with little time cost to their clinical workload . List of experts ranked by and hot linked specifically to the number of publications authored where the science achieved a significant clinical outcome or disease understanding (as opposed to simply commenting on a condition) . List of mathematically related diseases that share network properties with target disease for illumination of both common mechanisms of pathogenesis and cure: Enables drug discovery in professional pharma versions . Interactive Network Graph for scientific visualization of the nearest neighbor clouds of evidence illuminating the biological components of linked diseases and cures. Double Clicking nodes extends graph connectivity. Physician Outputs can be used without interruption in the clinical workflow if hot linked by HL7 Info Button right into any major EMR (Epic, VA Vista, GE Centricity, Cerner et al) and include additionally: . Instant presentation of evidence-based Meta-Analytic graph that has computed relative drug efficacy for every agent that has ever achieved a successful clinical outcome for the target disease . Frequency distribution counts for the number of independent studies generating the findings . Outcomes weighted for clinical success, derived from formal trials and studies, with Generic vs Branded comparisons . Related disease tables that quantitatively illuminate comorbidities and shared curative agents . History Icons that show the evidence over time and provide a relative indicator of global use and safety Drill down to abstract content, auto-report generation documenting the evidence audit trail, and Data Export to Formulary Optimization Systems require Professional Use registration and license fee. Pharmaceutical Research with University and Industry Partners: System Extensibility Deeper and direct integration of all the NLM Entrez databases into the system CA-DDD model for Computer Aided Drug Discovery and Development with the following goal: . Dramatically cut the cost of time and capital required to bring 1 new safe and effective agent to market: From Typically 1-1.5 billion dollars and 10-14 years to: $300 million/3 years. From 2009-2011 CureHunter staff scientists gave 4 university public lectures on the ability of the machine to self-discover new cures for human disease: See PDFs for details. Thank you NLM.