Introduction

In-silico retrosynthesis tools are invaluable in modern drug discovery workflows, accelerating route design and hypothesis generation. Yet, while these platforms enable rapid exploration of synthetic possibilities, their outputs are not infallible. Without careful oversight, chemists may accept suboptimal or impractical plans, leading to inefficiencies or outright failure in the lab. This article examines five common retrosynthesis analysis mistakes and offers practical guidance for navigating them.

 

Mistake 1 – Overcomplicating the Synthetic Route

Description: While retrosynthesis tools can rapidly generate diverse synthetic options, they may sometimes propose unnecessarily complex sequences. These routes can include avoidable steps—such as redundant protection/deprotection cycles or indirect detours—that aren’t always optimal in practice.

Impact: Without strategic oversight, software-generated routes may include inconsistent or unnecessary protection strategies that don’t account for stepwise orthogonality or long-range planning. For example, a CASP tool might introduce a protecting group in one step and suggest removing it shortly afterward—without considering whether it could have been maintained across multiple steps or avoided entirely. Such fragmented logic can increase operational complexity, step count, and risk of failure in the lab.

How to Avoid: Chemists should consider the route as a whole to build a cohesive protecting group strategy and minimize unnecessary conversions.  Iteratively refining the route to eliminate unnecessary operations ensures a more efficient path to target.

 

Mistake 2 – Ignoring Reaction Feasibility and Side Reactions

Description: Computational retrosynthesis often assumes idealized conditions and fails to flag side reactions, low-yielding steps, or operational hazards. Users may trust suggested reactions without validating their practicality.

Impact: Unforeseen side products or poor yields can compromise route viability. For instance, lithium-halogen exchange might be proposed without noting homocoupling risks under certain conditions. Such oversights can derail synthetic execution.

How to Avoid: Cross-reference proposed reactions with literature precedent or reaction databases. Platforms like SYNTHIA® may provide idea suggestions, but chemists must still verify reaction robustness. Consulting colleagues or process chemists can also uncover practical limitations early in planning.

 

Mistake 3 – Neglecting Stereochemistry and Chirality

Description: Some CASP tools inadequately handle chiral centers, resulting in racemic proposals or unspecified stereochemical outcomes.

Impact: In drug development, producing the wrong enantiomer or a racemate instead of a single stereoisomer can render the route unsuitable. Ignoring stereochemical control at key steps may necessitate costly rework or challenging purification steps.

How to Avoid: Explicitly define stereochemical constraints during planning. Favor routes that incorporate chiral catalysts, auxiliaries, or enantiopure building blocks. Chemists must ensure that each step maintains or introduces the correct stereochemistry with justified selectivity.

 

Mistake 4 – Failing to Verify Starting Material Availability

Description: Some retrosynthetic platforms generate routes that terminate at intermediates assumed to be “starting materials,” but which aren’t actually purchasable. Many tools limit retrosynthesis depth (e.g., stopping after three or four steps), without validating whether the terminal fragments are truly commercially available. This can result in synthetic plans that appear complete but ultimately rely on inaccessible compounds.

Impact: If the proposed "starting" materials are not procurable, the route becomes non-actionable and requires last-minute redesigns or additional upstream synthesis. Moreover, relying on virtual catalogs—common in some platforms—may introduce compounds with long lead times or uncertain synthetic feasibility, further delaying progress.

How to Avoid: Always confirm the availability of proposed building blocks using real-time supplier databases or internal inventory systems. SYNTHIA® offers an advantage here by integrating verified commercial catalogs—ensuring that suggested starting materials are real, orderable compounds rather than theoretical entries. In some cases, CASP tools can even highlight starting materials that chemists may have overlooked, streamlining the route by skipping unnecessary steps. Leveraging this capability requires a balance of trust in the software and verification through procurement channels.

 

Mistake 5 – Overreliance on Software without Expert Judgment

Description: A pervasive risk is treating CASP outputs as authoritative rather than advisory. Algorithms may overlook creative human disconnections or propose routes aligned with scoring functions, not practical constraints.

Impact: Blindly trusting software can result in suboptimal choices—e.g., obscure reaction types or roundabout pathways that a trained chemist would avoid. It may also mask opportunities for simplification or better alignment with project priorities (e.g., cost, safety).

How to Avoid: Maintain a human-in-the-loop approach at every stage. Retrosynthesis tools are most effective as ideation aids—not replacements—for chemical expertise. Chemists bring critical context that algorithms lack: practical knowledge of reagent stability, equipment limitations, scale-up concerns, and real-world reaction behavior. Incorporating this firsthand lab experience allows users to identify unrealistic proposals, streamline routes, and anticipate downstream challenges. Comparing multiple CASP-generated routes and refining them based on lab realities and strategic goals ensures the selected pathway is not just theoretically sound but practically viable. Ultimately, the most successful syntheses emerge from the synergy between computational breadth and human judgment.

 

Closing Thoughts

While in-silico retrosynthesis platforms like SYNTHIA® are transforming synthetic planning, their effective use demands critical engagement from users. Avoiding common pitfalls—from route overcomplication to stereochemical neglect—ensures that computational designs translate into viable laboratory routes. The best outcomes emerge when artificial intelligence and human intuition work in concert, combining algorithmic reach with chemical insight to create practical, innovative, and efficient syntheses.

 

References

1. Maziarz K, Tripp A, Liu G, et al. Re-evaluating Retrosynthesis Algorithms with Syntheseus. arXiv. (2023). https://arxiv.org/html/2310.19796v3
2. Torren-Peraire, P., Verhoeven, J., Herman, D. et al. Improving route development using convergent retrosynthesis planning. J Cheminform 17, 26 (2025). https://doi.org/10.1186/s13321-025-00953-1
3. MilliporeSigma. Overcoming Key Challenges in Drug Discovery. Lab Manager. (2022). https://www.labmanager.com/overcoming-key-challenges-in-drug-discovery-28992