Revealing the Impact of Genomic Alterations on Cancer Cell Signaling with an Interpretable Deep Learning Model.

Cancer is a disease of aberrant cellular signaling resulting from somatic genomic alterations (SGAs). Heterogeneous SGA events in tumors lead to tumor-specific signaling system aberrations. We interpret the cancer signaling system as a causal graphical model, where SGAs affect signaling proteins, propagate their effects through signal transduction, and ultimately change gene expression.

An interpretable deep learning framework for genome-informed precision oncology.

Cancers result from aberrations in cellular signaling systems, typically resulting from driver somatic genome alterations (SGAs) in individual tumors. Precision oncology requires understanding the cellular state and selecting medications that induce vulnerability in cancer cells under such conditions. To this end, we developed a computational framework consisting of two components: 1) A representation-learning component, which learns a representation of the cellular signaling systems when perturbed by SGAs, using a biologically-motivated and interpretable deep learning model.

Machine learning based algorithms to impute PaO from SpO values and development of an online calculator.

We created an online calculator using machine learning (ML) algorithms to impute the partial pressure of oxygen (PaO)/fraction of delivered oxygen (FiO) ratio using the non-invasive peripheral saturation of oxygen (SpO) and compared the accuracy of the ML models we developed to published equations. We generated three ML algorithms (neural network, regression, and kernel-based methods) using seven clinical variable features (N = 9900 ICU events) and subsequently three features (N = 20,198 ICU events) as input into the models. Data from mechanically ventilated ICU patients were obtained from the publicly available Medical Information Mart for Intensive Care (MIMIC III) database and used for analysis.

De novo Prediction of Cell-Drug Sensitivities Using Deep Learning-based Graph Regularized Matrix Factorization.

Application of artificial intelligence (AI) in precision oncology typically involves predicting whether the cancer cells of a patient (previously unseen by AI models) will respond to any of a set of existing anticancer drugs, based on responses of previous training cell samples to those drugs. To expand the repertoire of anticancer drugs, AI has also been used to repurpose drugs that have not been tested in an anticancer setting, i.e.

Pharmacokinetics and pharmacodynamics evaluation of a thermosensitive chitosan based hydrogel containing liposomal doxorubicin.

In situ gelling thermosensitive hydrogel formulation has been reported to effectively sustain the release of macromolecules for a long time. However, the low-molecular-weight hydrophilic drugs, such as doxorubicin (DOX), are not suitable for intratumoral injection because the release will complete within one day. In this study, liposomal doxorubicin (LipDOX) was added into the hydrogel to form a novel thermosensitive formulation which prolonged the sustained release of DOX.

Biotin-Conjugated Multilayer Poly [D,L-lactide-co-glycolide]-Lecithin-Polyethylene Glycol Nanoparticles for Targeted Delivery of Doxorubicin.

Multilayer nanoparticle combining the merits of liposome and polymer nanoparticle has been designed for the targeted delivery of doxorubicin (DOX) in cancer treatment. In this study, DOX-PLGA-lecithin-PEG-biotin nanoparticles (DOX-PLPB-NPs) were fabricated and functionalized with biotin for specific tumor targeting. Under the transmission electron microscopy observation, the lipid layer was found to be coated on the polymer core.

Comparative study on pharmacokinetics of a series of anticholinergics, atropine, anisodamine, anisodine, scopolamine and tiotropium in rats.

The compound series of traditional anticholinergics [atropine (Atr), anisodamine (Ani), anisodine (AT3), and scopolamine (Sco)], naturally occurring belladonna alkaloid, have been approved for numerous therapeutic uses since 1970s. Tiotropium, a novel M receptor antagonist for the treatment of chronic obstructive pulmonary disease, was structurally modified based on atropine-like drugs. Clinical phenomena suggested that the changes of substituent group were related to the pharmacokinetic and pharmacodynamic characteristics of the agents.

Comparison of pharmacokinetics, tissue distribution and pharmacodynamics of liposomal and free doxorubicin in tumour-bearing mice following intratumoral injection.

Objectives: The clinical application of doxorubicin (DOX) is limited by severe systemic side effects. The aim of this study was to develop a strategy that combined the liposomal DOX (LipDOX) and intratumoral injection to reduce the toxicity and enhance the antitumor efficiency.

Methods: The pharmacokinetics, tissue distribution and pharmacodynamics of LipDOX compared with free DOX were investigated by intratumoral injection in murine H22 hepatoma-bearing mice at a dose of 20 mg/kg body weight.

Efficacy, pharmacokinetics, and biodistribution of thermosensitive chitosan/β-glycerophosphate hydrogel loaded with docetaxel.

Docetaxel (DTX) is a widely used anticancer drug for various solid tumors. However, its poor solubility in water and lack of specification are two limitations for clinical use. The aim of the study was to develop a thermosensitive chitosan/β-glycerophosphate (C/GP) hydrogel loaded with DTX for intratumoral delivery.

In vitro cytotoxicity, pharmacokinetics and tissue distribution in rats of MXN-004, a novel conjugate of polyethylene glycol and SN38.

1.  MXN-004 is a water-soluble PEGylated 7-ethyl-10-hydroxy-camptothecin (SN38). The aim of this study was to evaluate the in vitro cytotoxicity of MXN-004 and investigate pharmacokinetics and tissue distribution of MXN-004 and its active metabolite SN38 in rats.

Pharmacokinetics study of hemin in rats by applying (58)Fe-extrinsically labeling techniques in combination with ICP-MS method.

Iron is a challenging element due to its high background in various matrixes including blood, tissues even in the air and it is urgent to develop a method for the accurate determination of iron in bio-samples. After optimization of mass spectrometric conditions using collision cell technology and compensating for interference using a mathematical correction equation, an inductively coupled plasma mass spectrometry (ICP-MS) method for the quantitative determination of (58)Fe originating from hemin extrinsically labeled avoiding endogenous interference was developed. After a single step of dilution, analysis of each sample was completed within 1.

Contributions of intestine and plasma to the presystemic bioconversion of vicagrel, an acetate of clopidogrel.

Purpose: To investigate the contributions of intestine and plasma to the presystemic bioconversion of vicagrel, and track its subsequent bioconversion to 2-oxo-clopidogrel in vivo and in vitro to rationalize the design of vicagrel, an acetate analogue of clopidogrel.

Methods: The concentration-time profiles of 2-oxo-clopidogrel and active metabolite (AM) in presystem and circulation system was determined in the cannulated rats. Also, the rat intestinal S9 and human intestinal microsomes were conducted to examine the formation of 2-oxo-clopidogrel and AM.

Pharmacokinetics, tissue distribution, and plasma protein binding study of platinum originating from dicycloplatin, a novel antitumor supramolecule, in rats and dogs by ICP-MS.

Dicycloplatin, as a new antitumor supramolecule, was considered to have higher solubility and higher stability compared with carboplatin. The aim of the present study was to evaluate the pharmacokinetic characteristics of platinum originating from dicycloplatin. A rapid, sensitive, and specific method with inductively coupled plasma mass spectrometry (ICP-MS) has been developed for the determination of platinum in bio-samples.