Preladenant

Immunotherapy is a promising cancer treatment strategy. In contrast, programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) inhibitors are associated with low response rates and are only useful in a small group of cancer patients. A combination of treatments may be effective for overcoming this clinical issue. Preladenant is an adenosine (ADO) receptor inhibitor that can block the ADO pathway and improve the tumor microenvironment (TME), thereby enhancing the immunotherapeutic effect of PD-1 inhibitors. However, its poor water solubility and low targeting limit its clinical applications. We designed a PEG-modified thermosensitive-liposome (pTSL) loaded with ADO small molecule inhibitor preladenant (P-pTSL) to overcome these problems and enhance the effect of PD-1 inhibitor on breast cancer immunotherapy. The prepared P-pTSL was round and uniformly distributed with a particle size of (138.9 ± 1.22) nm, PDI: 0.134 ± 0.031, and zeta potential (-10.1 ± 1.63) mV; preladenant was released slowly at 37 °C but released fast at 42 °C from P-pTSL, which was 76.52 ± 0.44%. P-pTSL has good long-term and serum stability and excellent tumor-targeting ability in mice. Moreover, the combination with PD-1 inhibitor significantly enhanced the anti-tumor effect, and the improvement of related factors in serum and lymph was more obvious under the condition of 42 °C thermotherapy in vitro.

The clinical impact of therapeutic interventions in Parkinson's disease is often measured as a reduction in OFF-time when the beneficial effects of the standard-of-care L-DOPA formulations wanes off. We investigated the pharmacodynamic interactions of augmentation therapy to standard-of-care using a quantitative systems pharmacology (QSP) model of the basal ganglia motor circuit, essentially a computer model of neuronal firing in the different subregions with anatomically informed connectivity, cell-specific expression of 17 different G-protein coupled receptors and corresponding coupling to voltage-gated ion channel effector proteins based on experimentally observed intracellular signaling. The calculated beta/gamma (b/g) power spectrum of the local field potentials in the subthalamic nucleus was previously calibrated on the clinically relevant Unified Parkinson's Disease Rating Scale (UPDRS). When combining this QSP model with PK modeling of different formulations of L-DOPA, we calculated the b/g fluctuations over a 16 h awake period and used a weighted distance from a specific threshold to determine the cumulative liability of OFF-Time. Prediction of OFF-time with clinical observations of different L-DOPA formulations showed a significant correlation. Simulations show that augmentation with the adenosine A_2A antagonist preladenant reduces OFF-time with 6 min for carbidopa/levodopa 950 mg 5-times daily to 37 min for 100 mg L-DOPA - 3 or 5 times daily. Exploring delays between preladenant and L-DOPA intake did not improve the outcome. Hypothetical A_2A antagonists with an ideal PK and pharmacology profile can achieve OFF-Time reductions ranging from 9.5 min with DuoDopa to 55 min with low dose L-DOPA formulations. Combination of the QSP model with PK modeling can predict the anticipated OFF-Time reduction of novel A2A antagonists with standard of care. With the large number of GPCR in the model, this combination can support both the design of clinical trials with new therapeutic agents and the optimization of combination therapy in clinical practice.