Safety and efficacy constitute the major criteria governing regulatory approval of any new drug. The best method to maximize safety and efficacy is to deliver a proven therapeutic agent with a targeting ligand that exhibits little affinity for healthy cells but high affinity for pathologic cells. The probability of regulatory approval can conceivably be further enhanced by exploiting the same targeting ligand, conjugated to an imaging agent, to select patients whose diseased tissues display sufficient targeted receptors for therapeutic efficacy. The focus of this Review is to summarize criteria that must be met during design of ligand-targeted drugs (LTDs) to achieve the required therapeutic potency with minimal toxicity. Because most LTDs are composed of a targeting ligand (e.g., organic molecule, aptamer, protein scaffold, or antibody), spacer, cleavable linker, and therapeutic warhead, criteria for successful design of each component will be described. Moreover, because obstacles to successful drug design can differ among human pathologies, limitations to drug delivery imposed by the unique characteristics of different diseases will be considered. With the explosion of genomic and transcriptomic data providing an ever-expanding selection of disease-specific targets, and with tools for high-throughput chemistry offering an escalating diversity of warheads, opportunities for innovating safe and effective LTDs has never been greater.
Keyphrases
- cancer therapy
- drug delivery
- induced apoptosis
- high throughput
- end stage renal disease
- cell cycle arrest
- chronic kidney disease
- endothelial cells
- single cell
- oxidative stress
- ejection fraction
- gene expression
- high resolution
- emergency department
- newly diagnosed
- transcription factor
- drug release
- prognostic factors
- cell death
- gold nanoparticles
- photodynamic therapy
- peritoneal dialysis
- signaling pathway
- endoplasmic reticulum stress
- copy number
- cell proliferation
- patient reported
- protein protein
- rna seq
- locally advanced
- data analysis
- deep learning
- tyrosine kinase
- lymph node