Modeling thrombus growth in pathological flows allows evaluation of risk under patient-specific pharmacological, hematological, and hemodynamical conditions. We have developed a 3D multiscale framework for the prediction of thrombus growth under flow on a spatially resolved surface presenting collagen and tissue factor (TF). The multiscale framework is composed of four coupled modules: a Neural Network (NN) that accounts for platelet signaling, a Lattice Kinetic Monte Carlo (LKMC) simulation for tracking platelet positions, a Finite Volume Method (FVM) simulator for solving convection-diffusion-reaction equations describing agonist release and transport, and a Lattice Boltzmann (LB) flow solver for computing the blood flow field over the growing thrombus. A reduced model of the coagulation cascade was embedded into the framework to account for TF-driven thrombin production. The 3D model was first tested against in vitro microfluidics experiments of whole blood perfusion with various antiplatelet agents targeting COX-1, P2Y1, or the IP receptor. The model was able to accurately capture the evolution and morphology of the growing thrombus. Certain problems of 2D models for thrombus growth (artifactual dendritic growth) were naturally avoided with realistic trajectories of platelets in 3D flow. The generalizability of the 3D multiscale solver enabled simulations of important clinical situations, such as cylindrical blood vessels and acute flow narrowing (stenosis). Enhanced platelet-platelet bonding at pathologically high shear rates (e.g., von Willebrand factor unfolding) was required for accurately describing thrombus growth in stenotic flows. Overall, the approach allows consideration of patient-specific platelet signaling and vascular geometry for the prediction of thrombotic episodes.

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We have employed a computer-aided approach to select and design task-specific organic solvents for the liquid-liquid extraction of ephedrine from its aqueous solution. We have identified three solvent performance indicators (SPIs) as the shortlisting criteria for solvents with desirable properties: high ephedrine solubility; low solvent loss; and high partition coefficient. Other properties that were considered include octanol-water partition coefficient and toxicity, which give a measure of the safety/health/environmental (SHE) impacts, and liquid viscosity, which is an important process design parameter. We have first analyzed the trends in these SPIs for a range of common organic solvents. Toluene (currently employed for the extraction of R-phenylacetylcarbinol, the precursor to ephedrine) has low solvent loss but relatively poor values of the other SPIs for ephedrine extraction, though with a relatively benign SHE impact. We are unable to identify a solvent (from the list of common organic solvents) that satisfies all the shortlisting criteria for use in the pharmaceutical industry and this provided the motivation for the design of task-specific solvents. We have designed organic solvents (acyclic aliphatic, aromatic with one side chain attachment, and aromatic with two side chain attachments) with superior values of SPIs than the reference solvent, toluene. We have employed limiting values on the melting and boiling points to ensure the designed solvents are liquids at the operating conditions. Designed aliphatic compounds contain the chloro-group(s), whereas there are aromatic solvents without the chloro-groups with better SPIs than toluene. Designed solvents without chloro-groups may be considered as the starting point for further screening experiments.