RICHMOND, Virginia, May 12, 2014 – algorithmRx, headquartered in Richmond, Virginia, announced today that it has been awarded a research grant from the National
Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) as part of the NIH’s Small Business Innovation Research (SBIR) program.
This new two-year grant is for nearly $1.5 million with $910,888 approved for the first year. The grant will fund further research related to algorithmRx’s predictive healthcare
algorithm, aRx Statin Advisor, which is one in a suite of novel, patent-pending, healthcare algorithms designed to improve the medication management of common
chronic health conditions. aRx Statin Advisor is an evidence-based clinical decision-support system (CDSS) designed to assist clinicians in selecting the most effective
statin and dose regimen for patients with high LDL-cholesterol (“LDL-C” or “bad cholesterol”).

High LDL-C is a major, modifiable risk factor for cardiovascular disease (CVD) which is the number one cause of death in the US. The Centers for Disease Control and
Prevention estimate that 71 million people in the US have high levels of bad cholesterol, with less than half (34 million) being treated with one of seven statin drugs, such as
Lipitor ® or Zocor ®. However, one-third of patients treated never reach their LDL-C reduction goal, and half of all 71 million patients receive no treatment or have
abandoned treatment, resulting in 48 million patients with untreated or inadequately treated levels of bad cholesterol. New recommended guidelines may increase markedly
the number of patients on statins.

Statins are remarkably effective at reducing LDL-C cholesterol levels and the resultant CVD risk, but many patients never achieve their goal because they are not receiving the
most effective statin/dose combination for their particular situation.

With seven different statins, each available in four or five different doses, and no evidence-based selection tool available, there is a low chance that the initial statin/dose combination chosen by a healthcare provider will achieve the patient’s LDL-C goal. Factors that contribute to suboptimal treatment include adverse effects experienced by the patient and poor medication adherence, each of which can be reduced or eliminated by better matching the statin and dose with the individual.

aRx Statin Advisor is the first clinical decision-support system to use an evidence-based, precise, personalized medicine approach to resolve this dilemma. aRx Statin Advisor is a complex multiple regression-based algorithm with a simple user interface. Utilizing numerous data variables that are readily available from a patient’s electronic health record (EHR), aRx Statin Advisor compares a patient’s results against those of millions of other patients who have been treated with statins. aRx Statin Advisor provides a matrix of statin/dose combinations in descending order of probability that the patient will reach his/her personal LDL-C goal. All of this information is delivered in real-time during a routine patient office visit.

aRx Statin Advisor can be used by trained healthcare personnel (e.g., physician assistants and nurses), thus offloading physician time and cost during long-term treatment to maintain each patient at his or her target level of LDL-C. By identifying the right statin in the right dose the first time, aRx Statin Advisor can reduce the time and cost associated with reaching and maintaining target LDL-C levels. Thus, aRx Statin Advisor could also improve medication adherence The associated healthcare cost savings are estimated to be hundreds of millions of dollars annually in the US alone.

According to Lenn Murrelle, PhD, Managing Partner of algorithmRx, “This new NHLBI/NIH funding will allow aRx Statin Advisor to progress to the next stage and will be the final step towards commercialization.” Dr. Murrelle further explained that the new research will be focused in five areas.

  • An expanded retrospective EHR-based study will be conducted among millions of patients representing the US population of statin users.
  • The results of this study will help fine-tune the predictive algorithm and create a more robust aRx Statin Advisor.
  • Healthcare providers in a primary-care setting that is part of an Accountable Care Organization (ACO) will beta test aRx Statin Advisor to evaluate its functional utility and user interface.
  • A detailed healthcare economics study will be completed to confirm early estimates of the significant potential healthcare cost savings from aRx Statin Advisor.
  • Genomic markers will be investigated to further improve the predictive power of aRx Statin Advisor and expand its utility.

algorithmRx previously received funding from NHLBI for an initial retrospective study using healthcare claims data from approximately 77 million statin prescriptions within the Veterans Health Administration. The company also received funding from the Commonwealth of Virginia’s Center for Innovation Technology.

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