Accelerated Repurposing and Drug Development of Pulmonary Hypertension Therapies for COVID-19 Treatment Using an AI-Integrated Biosimulation Platform

Figures

• 

  Figure 1. Potential model for the combinatorial actions of angiotensin-converting enzyme inhibitors (ACEi) and calcium channel blockers (CCBs) on SARS-CoV-2 infection, replication, and proinflammatory response. ACEi acting indirectly through ACE2 and the mitochondrial assembly 1 (MAS), ATR2 axis imparts an anti-inflammatory and anti-fibrotic response, while CCBs acts at various steps, restores intracellular Ca2+ flux, consequently inhibiting post-infection virus internalization and genome replication. Both ACEi and CCBs potentially can induce a synergistic anti-inflammatory and anti-fibrotic response in the attenuation of the “cytokine storm”.

• 

  Figure 2. Convergence onto discrete parameter combinations during coarse optimization for (A) Verapamil, (B) Spirapril, (C) Lisinopril, (D) Lacidipine, and (E) Captopril. Relative cost on the y-axis is calculated as: Cost_relative = AAFECmax*AAFEtmax*AAFEAUC where AAFECmax, AAFEtmax, AAFEAUC—absolute average fold error for Cmax, Tmax and AUC predictions.

• 

  Figure 3. Dose and route-of-administration dependent prediction of compound plasma concentration for (A) Verapamil (i.v.), (B) Spirapril (p.o.), (C) Lisinopril (p.o.), (D) Lacidipine (p.o.), and (E) Captopril (i.v.). Dashed lines correspond to BIOiSIM simulation outputs. Error bars and individual data points were digitized from the original publications (49,51,55,56,58) and correspond to standard error/standard deviation, as presented in the original work.

• 

  Figure 4. Prediction of the site-specific distribution of (A) Verapamil (i.v.), (B) Spirapril (p.o.), (C) Lisinopril (p.o.), (D) Lacidipine (p.o.), and (E) Captopril (i.v.) to tissues implicated in COVID-19 replication and pathogenesis. Subject conditions are described in Table 3.

• 

  Figure 5. Metrics for candidate compound identification unitilizing internal database of small molecule PK. The numbers in blue boxes correspond to the number of compounds identified as acceptable during each stage of curatrion.

• 

  Figure 6. Diagram of modeling approach taken that extends beyond pharmacokinetic modeling of compound disposition and can explore more complex viral and combination effects.