A first-in-human study of the novel metabolism-based anti-cancer agent SM-88 in subjects with advanced metastatic cancer.

Purpose SM-88 (D,L-alpha-metyrosine; racemetyrosine) is a novel anti-cancer agent, used with melanin, phenytoin, and sirolimus (SMK Therapy). This pilot first-in-human study characterized the safety, tolerability, and efficacy of SMK Therapy in subjects with advanced metastatic cancer. Methods All subjects (n = 30) received SMK Therapy for an initial 6 week Cycle (5 days on, 2 off per week) and continued if well tolerated. Safety signals, clinical response, overall survival, progression free survival (PFS), and quality of life changes were assessed. Results The most common drug related adverse events were hyperpigmentation and rash. All drug related adverse events were mild to moderate in intensity. Following treatment with SMK Therapy, 4 subjects achieved complete response, 6 partial response, and 17 stable disease according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 (total clinical benefit 90%). Responses were observed within 6 weeks, and continued to improve, with 3 complete and 3 partial responders achieving best response after at least 3.2 months. Durable stable disease was observed, lasting a median duration of 11 months (range 1-31 months). Median overall survival for all subjects was 29.8 months, and median PFS was 13 months. Following 6 weeks of treatment, most (83.3%) subjects showed an improvement in Eastern Cooperative Oncology Group (ECOG) score and an improvement in the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ 30) global health status (baseline 61.2 ± 25.0; end of Cycle 1 80.7 ± 14.7; n = 29; p < 0.001). Conclusions The results of this study support continued development of SM-88.

Thinking science with thinking machines: The multiple realities of basic and applied knowledge in a research border zone.

Some scholars dismiss the distinction between basic and applied science as passé, yet substantive assumptions about this boundary remain obdurate in research policy, popular rhetoric, the sociology and philosophy of science, and, indeed, at the level of bench practice. In this article, I draw on a multiple ontology framework to provide a more stable affirmation of a constructivist position in science and technology studies that cannot be reduced to a matter of competing perspectives on a single reality. The analysis is grounded in ethnographic research in the border zone of Artificial Intelligence science. I translate in-situ moments in which members of neighboring but differently situated labs engage in three distinct repertoires that render the reality of basic and applied science: partitioning, flipping, and collapsing. While the essences of scientific objects are nowhere to be found, the boundary between basic and applied is neither illusion nor mere propaganda. Instead, distinctions among scientific knowledge are made real as a matter of course.

A computational method for planning complex compound distributions under container, liquid handler, and assay constraints.

A systematic method for assembling and solving complex compound distribution problems is presented in detail. The method is based on a model problem that enumerates the mathematical equations and constraints describing a source container, liquid handler, and three types of destination containers involved in a set of compound distributions. One source container and one liquid handler are permitted in any given problem formulation, although any number of compound distributions may be specified. The relative importance of all distributions is expressed by assigning weights, which are factored into the final mathematical problem specification. A computer program was created that automatically assembles and solves a complete compound distribution problem given the parameters that describe the source container, liquid handler, and any number and type of compound distributions. Business rules are accommodated by adjusting weighting factors assigned to each distribution. An example problem, presented and explored in detail, demonstrates complex and nonintuitive solution behavior.