Computational studies and literature-validated simulation experiments.
Each study lives in its own subdirectory with a preset.toml, scripts, scenarios, and results.
source ~/biodynamo/build/bin/thisbdm.sh
# Diabetic treatment comparison (baseline + 8 treatments, ~3-4h)
./studies/diabetic-wound/treatment.sh
# Adaptive combo search (surrogate-guided, ~30-45min)
./studies/diabetic-wound/adaptive.sh
# Skin type comparison (normal vs aged vs diabetic)
./studies/wound/skin-comparison.sh
# Tumor growth kinetics
./studies/tumor/study.sh
# Experiment scenarios (7 experiments)
./studies/run-scenarios.sh| Script | Python backend | Description |
|---|---|---|
| diabetic/treatment.sh | treatment_study.py | Baseline + 8 treatments, Excel workbook |
| diabetic/adaptive.sh | adaptive_study.py | Surrogate-guided combo search with synergy detection |
| wound/skin-comparison.sh | batch/batch.py | Normal / aged / diabetic skin profiles |
| tumor/study.sh | batch/batch.py | BCC/SCC growth rate validation |
| run-scenarios.sh | scenario_runner.py | Experiment scenarios across all studies |
TOML-defined experiments in studies/diabetic-wound/scenarios/, each exploring a different axis of diabetic wound healing:
| Scenario | File | Configs | Runs |
|---|---|---|---|
| Severity spectrum | severity_spectrum.toml | 5 levels (0.5x to 1.5x) | 5/config |
| Biofilm infection | biofilm_infection.toml | 4 (control, early/late, +doxy) | 5/config |
| Treatment timing | treatment_timing.toml | 12 (3 treatments x 4 windows) | 5/config |
| Wound size | wound_size.toml | 4 (1.5mm to 8mm) | 5/config |
| Aged + diabetic | aged_diabetic.toml | 4 phenotypes | 5/config |
| Chronic wound (90d) | chronic_wound.toml | 4 (severe + biofilm + rescue) | 3/config |
| Immune tuning | immune_tuning.toml | 4 (restore one axis) | 5/config |
bash studies/run-scenarios.sh # all scenarios
bash studies/run-scenarios.sh studies/diabetic-wound/scenarios/wound_size.toml # single scenario
bash studies/run-scenarios.sh --quick # all with 2 runsTimeseries validated against published consensus curves (RMSE < 15%).
| Observable | Consensus CSV | Key sources | Condition |
|---|---|---|---|
| Wound closure | closure_kinetics_punch_biopsy.csv | Cukjati 2001, Gonzalez 2016 | Normal |
| Inflammation | inflammation_timecourse.csv | Eming 2007, Koh 2011 | Normal |
| Immune cells | immune_cell_kinetics.csv | Kim 2008, Rodero 2010 | Normal |
| Myofibroblasts | myofibroblast_kinetics.csv | Darby 2014, Desmouliere 1995 | Normal |
| Collagen | collagen_deposition.csv | Zhou 2013, Murphy 2012 | Normal |
| Diabetic closure | diabetic_closure_kinetics.csv | Mirza 2011, Louiselle 2021 | Diabetic |
| Diabetic inflammation | diabetic_inflammation_timecourse.csv | Wetzler 2000, Mirza 2011 | Diabetic |
| Diabetic immune cells | diabetic_immune_cell_kinetics.csv | Khanna 2010, Wang 2020 | Diabetic |
| Tumor growth | tumor_growth_rate.csv | Kricker 2014, Fijalkowska 2023, Sykes 2020 | Tumor |
Modules with parameter values sourced from literature (not timeseries-validated).
| Module | Status | Parameters | Key sources |
|---|---|---|---|
| Angiogenesis | Enabled | VEGF diffusion, sprout rate, capillary density | Schugart 2008 (10.1016/j.jtbi.2008.06.042), Flegg 2012 |
| MMP | Enabled | Decay, production rates, TIMP interaction | Nagase 1999, Ladwig 2002 (10.1067/mjd.2002.124601) |
| Fibronectin | Enabled | Deposition rate, degradation | Clark 1990, Grinnell 1984 |
| Scar | Enabled | Collagen-based scar scoring, remodeling | Ogawa 2017 (10.3390/ijms18030606), Gauglitz 2011 |
| Hemostasis | Disabled | Platelet plug, fibrin mesh, clotting cascade | Brass 2010, Reininger 2006 |
| Perfusion | Enabled | O2 transport, vascular delivery | Johnson 1971, Stucker 2002 |
| Dermis | Enabled | Dermal ECM, thickness, hydration | Braverman 2000, Singer 1999 |
| Treatment | Mechanism | Key sources | Parameters modified |
|---|---|---|---|
| Anti-inflammatory | Anti-TNF-alpha, accelerates M1-to-M2 | Goren 2007 | M1 decay, M2 transition |
| Combination | Multi-modal (anti-infl + HBO + doxy + moisture) | Composite | Multiple |
| Doxycycline | Sub-antimicrobial MMP inhibitor | Siqueira 2010, Smith 1999 | MMP production, collagen decay |
| Growth factor | Becaplermin (PDGF-BB) | Steed 2006, Smiell 1998 | KGF rate, chemotaxis |
| HBO | Hyperbaric oxygen therapy | Londahl 2010, Fedorko 2016 | O2 delivery, VEGF |
| Moisture | Advanced dressings (hydrogel/foam) | Junker 2013, Kannon 1995 | Water recovery, evaporation |
| MSC | Mesenchymal stem cell therapy | Cao 2017 | Immune modulation, growth factors |
| NPWT | Negative pressure wound therapy | Morykwas 1997, Armstrong 2005 | Perfusion, granulation |
Modules with implementation complete but disabled by default (awaiting calibration or validation data).
| Module | Config key | Sources | Notes |
|---|---|---|---|
| Biofilm | skin.biofilm.enabled |
James 2008, Bjarnsholt 2008, Davis 2008 | Bacterial colonization, immune evasion |
| pH | skin.ph.enabled |
Schneider 2007, Gethin 2007 | Wound bed pH gradient, enzyme activity |
| Hyaluronan | skin.hyaluronan.enabled |
Toole 2004, Stern 2006 | HAS2-driven HA synthesis, hydration |
| Elastin | skin.elastin.enabled |
Kielty 2002, Almine 2012 | Tropoelastin deposition, cross-linking |
| Hemostasis | skin.hemostasis.enabled |
Brass 2010, Reininger 2006 | Platelet activation, fibrin scaffold |
Areas with published mechanistic data that could extend the model.
| Feature | Biological basis | Candidate sources | Complexity |
|---|---|---|---|
| Temperature therapy | Accelerated enzymatic rates, vasodilation | Ikeda 2005, Kloth 2002 | Low |
| Oxygen therapy (topical) | Direct O2 application vs HBO | Gordillo 2007 | Low |
| pH treatment | Acidic dressings shift enzyme optimum | Schneider 2007 | Medium |
| HA treatment | Exogenous hyaluronan scaffolds | Tolg 2014, Voigt 2012 | Medium |
| Cellular senescence | SASP-driven chronic inflammation | Demaria 2014, Wilkinson 2019 | High |
| Oxidative stress | ROS-mediated tissue damage | Schafer 2008, Sen 2009 | High |
| Basement membrane | Laminin/collagen IV reassembly | Rousselle 2019 | High |
# Run literature validation on any metrics CSV
python3 literature/validate_all.py output/skibidy/metrics.csv
# Check source integrity (DOIs referenced in configs vs SOURCES.yaml)
python3 literature/check_sources.py
# 10-run batch consensus with validation
python3 batch/batch.py -n 10 --skin normal --study wound --validate
python3 batch/batch.py -n 10 --skin diabetic --study diabetic-wound --validatePre-generated results are included so you can inspect output without running simulations.
| Study | Example file | Description |
|---|---|---|
| Diabetic treatments | diabetic/example/ | 8-treatment comparison Excel workbook |
| Adaptive combos | diabetic/adaptive-example/ | Surrogate predictions + synergy analysis |