SBIR-STTR Award

The primary objective is to determine minimal sampling frequencies and study duration required to significantly differentiate hormonal secretory patterns between clinically distinct cohorts, via approximate entropy (ApEn), a quantification of sequential irregularity developed by the principal investigator. ApEn has been broadly applied within clinical endocrinology, providing complementary information to pulse detection methods. However, typical protocols employed to generate data sets suitable for 'pulsatility analysis' have required 60-300 samples, rendering such studies largely research (rather than clinical) methods, due primarily to considerable assay expense. In reanalysis of one published hormonal study database, we have realized dramatic reduction in the number of samples required to do discriminatory pulsatility analysis via ApEn. The purpose herein is to augment these finding to determine the breadth of this reductive capability. Such reduction in sampling requirements holds the potential to move pulsatility analysis from a primarily research basis to a clinically applicable protocol, in appropriate diagnostic and therapeutic contexts. Phase I focuses on reanalysis of two classes of tumoral subject data (Cushing's disease and acromegaly), plus younger vs. older male LH and testosterone secretory data.Proposed Commercial Application:Not avaliable

Thesaurus Terms:
endocrinology, hormone regulation /control mechanism, mathematical model, model design /development, secretion, statistics /biometry Cushing's syndrome, acromegaly, adrenocorticotropic hormone, diagnosis design /evaluation, endocrine disorder diagnosis, luteinizing hormone, somatotropin, testosterone clinical research, human data

The primary objective is to determine minimal sampling frequencies and study durations required to significantly differentiate hormonal secretory patterns between clinically distinct cohorts, via Approximate entropy (ApEn) and cross-ApEn, quantifications of sequential irregularity and two-variable asynchrony, respectively, developed by the principal investigator. ApEn and cross-ApEn have been broadly applied within endocrinology, complementarily to pulse detection methods. However, typical protocols employed to generate data sets suitable for 'pulsatility analysis' have required 60-300 samples, rendering such studies largely research (rather than clinical) methods, due primarily to considerable assay expense. In Phase I, via reanalyses of three published hormonal studies, we realized dramatic reduction in the number of samples required to do discriminatory pulsatility analysis via ApEn. In Phase II we will augment these findings to determine the breadth of this reductive capability, utilizing ApEn and cross- ApEn applied to tumoral settings, diabetes, and changes and disorders associated with aging and reproductive capacity. Such reduction in sampling requirements holds the potential to move pulsatility analysis from a primarily research basis to a clinically applicable protocol, in appropriate contexts. Phase III will commercialize this approach via incorporation of ApEn software into existing hormonal administration systems, and collaborations with pharmaceutical companies who manufacture the studied hormones. PROPOSED COMMERCIAL APPLICATIONS: Software development of an ApEn program for application to general endocrine hormone secretion time-series; incorporation of ApEn software into existing hormonal administration systems. Collaborations with pharmaceutical companies who manufacture estrogen, GnRH agonists, gonadotropins, testosterone and insulin