Synthesis Strategies — Cross-Cutting Comparison
This note compares the strategies a synthetic chemist actually chooses between when planning a target — convergent vs linear, choice of protecting groups, retrosynthesis tool, catalysis platform (transition-metal vs organo vs photoredox vs enzymatic vs electro), reactor mode (batch vs flow vs SPPS), and synthesis era exemplar — across every Chemistry library note that touches synthesis. Read each section’s table to see how a given dimension breaks down across topics; the final decision tree is the practical “which strategy do I pick for this target” view.
See also
- organic-chemistry-foundations
- medicinal-and-photo-chemistry
- biochemistry-foundations
- computational-chemistry-deep
- green-chemistry-and-process-intensification
- inorganic-chemistry
- polymer-chemistry
- supramolecular-and-host-guest-chemistry
- reagent-and-reaction-catalog
- functional-groups-and-solvents
1. The two architectural questions
Every total synthesis answers two architectural questions before a flask is touched.
- Convergent vs linear? A linear synthesis adds one piece at a time; total step count goes up linearly with size and yield decays geometrically (0.85^n at 85% per step → 20% at 10 steps, 4% at 20 steps). A convergent synthesis builds fragments in parallel and joins them late; the longest linear sequence is what controls overall yield, not the total step count. For any target above ~15 steps, convergent is mandatory.
- Protecting-group strategy? Bn (benzyl, hydrogenolysis), TBS/TBDPS (silyl, F⁻), Boc (acid), Fmoc (base), Cbz (H2), Ac (base), Bz (base), MOM/MEM (acid), allyl (Pd), PMB (DDQ/oxidation), THP (acid). Orthogonality means each protecting group can be removed without touching the others — a four-orthogonal set (e.g., Boc + Bn + TBS + Fmoc) covers most peptide and natural-product syntheses.
| Architectural choice | When to use | Example | Penalty if wrong |
|---|---|---|---|
| Linear | < 8 steps, all transformations high-yield, no large groups to add late | early-route discovery work | step count compounds; yield collapses |
| Convergent | > 12 steps, modular target, late-stage diversification | Taxol (Nicolaou, Holton), palytoxin (Kishi) | over-engineering for tiny targets |
| Block-synthesis (peptide, oligo, glycan) | repeating subunit | SPPS Merrifield, oligo synthesis | locked into available monomers |
| Combinatorial / DEL (DNA-encoded library) | screening (no scale-up intent) | hit-finding for medchem | not for resynthesis or scale |
| Biocatalysis | when wild-type enzyme matches functional-group operation | sitagliptin (Codexis–Merck transaminase 2010) | enzyme engineering cost |
| Flow chemistry | hazardous intermediates, photochemistry, fast exotherms | diazomethane in-situ, photoredox at scale | upfront capex; limited mixing for slow reactions |
2. Retrosynthetic analysis — the strategy layer
E. J. Corey’s retrosynthesis (Nobel 1990 in Chemistry, “for his development of the theory and methodology of organic synthesis”) is the formal strategy: dissect a target into precursors by reversing known reactions until commercial materials remain. The disconnections divide into:
- Synthon-based — Corey’s original. Identify electrophile/nucleophile pairs at strategic bonds.
- Functional-group-based — work backward from FG manipulations.
- Strategic-bond-based — Bertz, Hudlický measures of complexity; pick bonds whose disconnection maximally simplifies the graph.
- Transform-based (computer-aided) — match named reactions in a database, score by feasibility.
| Tool | Era | Approach | Status (2026) |
|---|---|---|---|
| LHASA (Corey, Harvard) | 1969–1980s | rule-based, expert-curated | discontinued; foundational |
| SYNTHIA (formerly Chematica, Grzybowski) | 2018+ (Sigma-Aldrich Merck KGaA) | rule-based + machine learning + ChemAxon | commercial, BIOVIA-grade |
| Reaxys + Synthia | 1990s+ (Elsevier acquired 2009) | reaction database (>50M reactions) + similarity search | dominant in industry |
| ASKCOS (MIT, Coley, Jensen 2018+) | open source | template-based neural retrosynth | research/open |
| AiZynthFinder (AstraZeneca 2020+) | open source | template-based, MCTS | research/pharma |
| Synthia + IBM RoboRXN (2019+) | cloud | combine retrosynthesis + robotic execution | early commercial |
| Chemical.AI / Innosynth | startups 2020+ | transformer-based reaction prediction | growing |
The state of the art in 2026 is hybrid — rule-based templates for common reactions, graph-neural-network or transformer prediction for novel disconnections, and beam-search/MCTS planning over the reaction graph. Grzybowski’s 2018 Nature paper “Efficient syntheses of diverse, medicinally relevant targets planned by computer and executed in the laboratory” demonstrated Chematica planning syntheses that human chemists then ran with no replanning. By 2025 Sigma-Aldrich’s Synthia (the productized Chematica) is integrated into Merck KGaA’s full medchem stack.
3. Total-synthesis exemplars — the historical curve
These syntheses are the field’s milestones. Each pushed at least one frontier and is taught as a strategic case study.
| Target | Year | Lead | Steps | Strategy | Lasting contribution |
|---|---|---|---|---|---|
| Strychnine | 1954 | R. B. Woodward (Harvard) | 28 (LLS) | mostly linear, classic ring-construction | first total synthesis of a complex alkaloid; founded “Woodward school” |
| Cholesterol | 1951 | Woodward | ~36 | mostly linear | first steroid total synthesis |
| Quinine | 1944 / 2001 confirmed | Woodward–Doering / Stork | varied | linear | resolved 1944 controversy; teaching example |
| Reserpine | 1956 | Woodward | 14 | convergent (early) | Woodward at his peak; stereocontrol via conformational analysis |
| Chlorophyll a | 1960 | Woodward + Strell | 55 | linear; modular ring construction | extended porphyrin chemistry |
| Vitamin B12 | 1973 | Woodward + Eschenmoser | ~70 (combined effort) | convergent, joint Harvard-ETH | the Mount Everest of total synthesis; ~100 chemists, ~12 years |
| Erythromycin A | 1981 | Woodward (posthumous) | 50+ | convergent | macrolide construction (Yamaguchi macrolactonization) |
| Palytoxin | 1994 | Y. Kishi (Harvard) | 140+ | hyperconvergent, 8 fragments | most complex natural product ever made; 64 stereocenters |
| Taxol | 1994 | Nicolaou (Scripps) / Holton (FSU); also Wender, Mukaiyama, Danishefsky | varied | distinct strategies — convergent, semisynthetic | five total + multiple semisynthetic routes; classic comparison study |
| Strychnine (modern) | 2011 | Vanderwal (UCI) | 6 | shortest known; Diels-Alder cascade | shows how RS + modern cat shrinks step counts |
| Avermectin | 1989 | Hanessian (Montreal) | 35+ | convergent | macrolide w/ challenging hexahydrobenzofuran |
| Eribulin (Halaven) | 2009 | Kishi (Eisai) | 62 | convergent | most complex marketed drug ever made; ~$200M/yr revenue |
| Sirolimus / rapamycin | 2003 | Nicolaou; later Wender, Smith, Danishefsky | 30+ | macrocyclic, convergent | mTOR inhibitor scaffold |
| Discodermolide | 2004 | Smith / Paterson / Schreiber / Novartis | 25+ | convergent + scaled to 60 g (Novartis) | rare example of scaled total synthesis for clinical trial |
| Vinblastine | 2009 | Boger (Scripps) | 11 | convergent dimerization | bio-inspired indole-indole coupling |
| Maoecrystal V | 2010 | Yang (HK) / Reisman / Danheiser | 17–25 | convergent | bridged terpene |
| Welwitindolinone A | 2011 | Garg (UCLA) / Rawal | 15 | convergent | indol benzofuran; combined photoredox-era thinking |
| Strychnos alkaloid family | 2020 | MacMillan + Sames | varied | photoredox-driven C–H | enabling-step contributions |
By the 2010s the field had matured to where the question was no longer “can we make X” but “can we make X in 5 steps with 30% yield from commercial materials”. Vanderwal’s 6-step strychnine (2011) crystallized this. Photoredox, organocatalysis, and C–H functionalization are why.
4. The catalysis platform spectrum — choose your bond-forming engine
The bond-forming engines that 2020-era chemists choose between, and the Nobel timeline:
| Era | Platform | Key chemists | Nobel | Footprint in synthesis (2026) |
|---|---|---|---|---|
| pre-1980 | classical (Grignard, aldol, Wittig, Diels–Alder) | Grignard 1912, Diels-Alder 1950, Wittig 1979 | many | foundational, still dominant for simple FG operations |
| 1980s | early TM cross-coupling | Negishi, Suzuki, Miyaura, Stille, Sonogashira | (2010 Heck/Negishi/Suzuki) | Pd-catalyzed C–C, every medchem program |
| 1990s | metathesis | Chauvin, Grubbs, Schrock | 2005 | RCM for macrocycles, CM for fragment joining |
| 1990s | asymmetric catalysis | Knowles, Noyori, Sharpless | 2001 | chiral hydrogenation, dihydroxylation, epoxidation |
| 2000s | organocatalysis | List, MacMillan | 2021 | iminium / enamine, Brønsted acid, NHCs |
| 2010s | C–H activation | Yu (Scripps), Sanford, Hartwig, Bergman | — | late-stage functionalization of complex scaffolds |
| 2010s | photoredox | MacMillan, Yoon (Wisc), Stephenson (UMich) | — | radical chemistry under mild conditions, Ru/Ir or organic dye |
| 2010s | flow chemistry | Jamison (MIT), Ley (Cambridge) | — | hazardous intermediates, photochem, on-demand |
| 2010s | electrochemistry | Baran (Scripps 2018+) | — | anodic oxidation of complex molecules; programmable potential |
| 2020s | biocatalysis (engineered) | Arnold (CalTech) | 2018 (directed evolution) | enzymes for stereo, FG, scalable |
| 2020s | click + bioorthogonal | Sharpless, Meldal, Bertozzi | 2022 | CuAAC + SPAAC for ligation, ADCs, conjugates |
| Platform | Best at | Watch out |
|---|---|---|
| Pd cross-coupling (Suzuki, Negishi, Buchwald-Hartwig) | sp²–sp² and Cl/N–H bonds, predictable | Pd residue in API (ICH Q3D limits) |
| RuO4/OsO4 (Sharpless dihydroxylation) | cis-diol from alkene | OsO4 toxicity |
| Sharpless asymmetric epoxidation | allylic alcohols → epoxides | substrate scope (needs allylic OH) |
| Noyori BINAP hydrogenation | β-ketoester → β-hydroxy ester (>99% ee) | sub costly, but proven on tonne scale (Takasago menthol 30 kt/yr) |
| Grubbs RCM | medium / large rings, late stage | E/Z selectivity in macrocycles |
| MacMillan iminium / List enamine | enantioselective α-functionalization of carbonyls | substrate scope |
| Yu C–H activation | unactivated C–H | ligand engineering nontrivial |
| MacMillan photoredox | radical chemistry under mild conditions | LED setup; lamp uniformity |
| Stephenson photoredox | radical cascades, late-stage | reproducibility cross-lab |
| Baran electrochemistry | reagent-free oxidation, scale | electrode passivation, undivided vs divided cell |
| Codexis transaminase (engineered) | β-chiral amine | enzyme engineering ROI |
| Sharpless–Meldal CuAAC | bioconjugation, conjugates | Cu in biological samples |
| Bertozzi SPAAC (DBCO-azide) | living-cell labeling, ADCs | DBCO cost |
5. Flow vs batch — when geometry matters
Batch is the default; flow earns its keep in specific situations.
| Situation | Flow wins because… | Examples |
|---|---|---|
| Hazardous intermediate | small volume in-situ, never accumulates | diazomethane (Ley), HN3, hydrazoic acid, F2, ozone |
| Fast exotherm | mm-scale heat transfer >100× batch | nitration, lithiation, organolithium |
| Photochemistry | thin film, uniform photon flux | [2+2], photoredox cascades (Stephenson, Booker-Milburn) |
| Multi-step telescoping | no intermediate isolation | Eli Lilly diphenhydramine flow (2014); Ley telescoped 1-naphtholol benzodiazepine |
| Continuous production | API on demand | Janssen prezista, Vertex multiple |
| Heterogeneous catalysis | packed-bed catalyst, no filtration | continuous hydrogenation (H-Cube) |
Major industrial flow installations: Vertex (Boston) — first FDA-approved continuous-manufacturing API (Orkambi, 2015). Janssen (Beerse, Belgium) — continuous prezista since 2016. Eli Lilly Kinsale (Ireland) — multiple oncology APIs in flow. Snapdragon Chemistry (Boston, acquired by Cambrex) — contract flow chemistry. The FDA Emerging Technology Team (ETT) explicitly endorses continuous manufacturing as the modernization target.
6. Solid-phase and parallel synthesis
| Method | Origin | Scale | Use |
|---|---|---|---|
| SPPS (solid-phase peptide synthesis) | Bruce Merrifield 1963 (Nobel 1984) | mg–g (lab), kg (CMC) | every peptide drug — semaglutide, liraglutide, tirzepatide, vasopressin agonists |
| Solid-phase oligonucleotide | Caruthers 1981 (phosphoramidite) | µg–g | every ASO, siRNA, mRNA primer |
| Glycan SPPS | Seeberger (MPI Potsdam) 2001+ | mg | research; commercial via GlycoUniverse |
| Parallel batch (medchem) | 1990s combichem | mg per compound | every medchem hit-to-lead campaign |
| DEL (DNA-encoded library) | Brenner-Lerner 1992; revived 2009 (X-Chem, GSK Encoded Library Technology) | 10^6–10^12 compounds | screening, not resynthesis |
| Microreactor parallel (Chemspeed, Mettler EasyMax, HEL, AMTechnology) | 2000s | mg–g | high-throughput experimentation in pharma |
For peptide drugs, SPPS is so dominant that the entire workflow (Fmoc-AA-OH purchase → automated couplings → resin cleavage → preparative HPLC purification → lyophilization → fill-finish) is industrialized. Semaglutide (Ozempic / Wegovy) is made at >50 t/yr by Novo Nordisk and PolyPeptide using Fmoc-SPPS, with the cost dominated by amino acid building blocks.
7. The “step count” floor
A useful mental model: every target has an irreducible step count set by the bond-graph complexity. Hudlický’s index, Bertz’s index, and the CSI (Computed Synthetic Intuition) index of Coley et al. (2018) all attempt to quantify it. Empirically, by 2020, the median total synthesis published in JACS / Nature / Science was ~18 LLS steps; the median published in 1990 was ~35. The drop is from RDRP (controlled radical), photoredox, C–H activation, and biocatalysis — each replaces several FG-interconversion steps with a direct bond-forming step.
8. Cost, scale, IP
| Synthesis decision | Drives | Penalty |
|---|---|---|
| Choice of chiral pool starting material | route + ee | not always available, or seasonally |
| Choice of resolution vs asymmetric catalysis | yield (50% max for resolution unless racemization-coupled) | resolution wastes the wrong enantiomer |
| Choice of biocatalysis vs metal catalysis | residual metal limits (Pd, Ru, Pt in API < 5 ppm per ICH Q3D) | biocat ROI on tonnage |
| Choice of solvent (CHEM21 guide, Pfizer green-chem) | E-factor, environmental | hexane and DMF banned in many EU contracts |
| Telescoping (no intermediate isolation) | E-factor + cycle time | regulatory burden (more impurities to qualify) |
| Patent landscape | route freedom | competing pharma patent your favorite step |
The CHEM21 solvent selection guide and Pfizer’s green-chemistry solvent guide are the operational tools. Ethanol, EtOAc, MIBK, acetone, water — preferred. DMSO, NMP, DMF, DMAc, DCM, CHCl3 — restricted. CCl4, benzene, Et2O — banned.
9. Modern catalysis era — 2020–2026
What’s new vs textbook organic chemistry:
- Photoredox + nickel dual catalysis (Doyle, MacMillan, Molander 2014+) — replaces palladium for sp³-sp² couplings; opens “metallaphotoredox” as a unified platform.
- Electrochemistry (Baran 2018+) — eliminates stoichiometric oxidants. Notable: ElectraSyn 2.0 (IKA / Scripps spinout) is in 1500+ academic labs by 2025; Baran’s papers explicitly include “make at-home” gear lists.
- Enzyme cascades — Codexis (transaminase for sitagliptin Januvia, 2010), Codex Bio for islatravir 2020, Merck + Codexis multi-enzyme cascade for molnupiravir 2021.
- Biocatalysis directed evolution (Arnold, Nobel 2018) — engineer the enzyme for the target, not the target for the enzyme.
- C–H activation late-stage functionalization (Yu, Engle, Sames, MacMillan) — change a hit compound late without re-doing the route.
- DEL (DNA-encoded libraries) — billions of compounds screened in a single afternoon; Vipergen, X-Chem, HitGen, Insilico’s DEL platforms.
- Generative chemistry (Insilico, Exscientia, Iktos, Schrödinger, BenevolentAI) — propose new structures from disease/target hypotheses; route designed by Synthia/ASKCOS; execute robotically (RoboRXN).
- 3D printed flow reactors (PHASTAR, ChemTrix, Vapourtec, Chemspeed) — bespoke residence times and mixing.
10. Decision tree — picking a synthesis strategy
What's the target?
├─ Single small molecule, novel scaffold (research / process)
│ ├─ < 8 steps → linear, classical, batch
│ ├─ 8–15 steps → convergent, batch with telescoping where safe
│ ├─ > 15 steps → highly convergent, late-stage diversification, RAFT/RDRP if polymer
│ └─ Complex stereocenters → asymmetric cat (BINAP, salen-Mn, organocat) or chiral pool
├─ Peptide drug
│ └─ Fmoc-SPPS (Merrifield); parallel or microwave; cleave + prep HPLC
├─ Oligonucleotide drug
│ └─ phosphoramidite SPPS (Caruthers); ASO/siRNA scale
├─ Macrocyclic natural product
│ └─ Yamaguchi macrolactonization or RCM (Grubbs); convergent fragments
├─ ADC payload + linker + antibody
│ ├─ Payload: classical or convergent synthesis
│ ├─ Linker: orthogonal protecting groups
│ └─ Conjugation: click (CuAAC or SPAAC)
├─ Bio-similar / generic API
│ └─ Reverse-engineer route from public patents; optimize on cost/PMI
├─ Hazardous reagent in chain
│ └─ Flow chemistry (diazomethane, lithiation, ozonolysis, nitration, photoredox)
├─ Continuous-manufacturing target
│ └─ Flow + telescoping; FDA Emerging Technology Team consultation
├─ Screening / hit-finding
│ └─ DEL (10^9 cmpds) or HTS (10^6 cmpds via combichem)
├─ Engineered enzymatic route exists
│ └─ Biocatalysis (Codexis, Merck, Novartis, BASF)
└─ Polymer / material target
→ See [[Sciences/Chemistry/_compare_polymerization_methods]]
Adjacent
- Polymerization — _compare_polymerization_methods for the polymer-specific synthesis-strategy view.
- Analytical — _compare_analytical-methods for proving you made what you intended.
- Computational chemistry — computational-chemistry-deep for DFT-aided mechanism, transition-state, retrosynthesis scoring.
- Green chemistry — green-chemistry-and-process-intensification for E-factor, atom economy, solvent guides, scCO2, ionic liquids.
- Medicinal chemistry context — medicinal-and-photo-chemistry for the drug-discovery framing.
- Pharma process scale-up — pharma-process-engineering for kg → tonne scale, GMP, ICH guidance.
- Polymer chemistry — polymer-chemistry for polymer-specific architectures.
- Inorganic / catalyst design — inorganic-chemistry for organometallic catalyst structure.
When to pick what
The fastest narrowing: simple → classical batch; complex → convergent + modern cat (photoredox, organocat, biocat, C–H); peptide → SPPS; oligo → phosphoramidite SPPS; macrocycle → RCM or Yamaguchi; hazardous → flow; scale-up commodity API → telescoped flow under FDA ETT; screening → DEL + AI retrosynthesis (Synthia/ASKCOS). The single biggest practical lesson of 2010–2026 is that step count matters less than route convergence — a 12-step convergent synthesis at 40% overall is almost always better than a 7-step linear at 30%, because the 12-step route ships kilograms while the 7-step route stalls at grams. Choose the catalyst platform that maximizes step economy at your target’s most strategic bond, then defend the rest with classical chemistry.