Lead optimization and drug-candidate selection

A drug must have sufficient oral bioavailability in humans otherwise clinical trials are not effective and drug development is then stopped.

Oral bioavailability is one of the most important properties in lead optimisation. Low drug-uptake in humans can result in high inter-individual variability and increases the risk of side-effects and toxicity.

IMPACT-F correctly ranks (prioritises) novel drug-candidates on human oral bioavailability.

A validation study was carried out containing thirty-three independent drug-candidates coming from different therapeutic areas such as cancer, antibacterial or antiviral infection, CNS, inflammation, gastrointestinal and renal diseases, metabolism related diseases and cardiovascular diseases.

The best drug-candidates with highest oral bioavailability were placed on top positions of the ranked list, whereas poor candidates with low drug uptake were found at the bottom of the list.

A low error and a good correlation was observed. Oral bioavailability predictions were as accurate as the common deviation between individual humans in a clinical trial.

IMPACT-F ranks compounds with global QSPR models so only drug structures are needed to carry out a prioritisation study for selecting leads and drug-candidates.

To use our prediction service or to obtain more information, please give us a call (+49 4921-993360) or send an email by clicking the button:

Pharmaceutical companies use IMPACT-F in different therapeutic areas such as diabetes, inflammation, antivirals, autoimmune diseases and cancer for selection and prioritisation of drug candidates, to optimise prodrugs and to evaluate oral bioavailability before clinical trials in humans, see recent collaborations.

The expert system reliably evaluates drug-candidates ranging across all therapeutic areas. The validation set included a CCR5 antagonist for treatment of rheumatoid arthritis, a p38 MAP-kinase inhibitor for treatment of acute coronary syndrome, four novel angiotensin II receptor blocker (antihypertensive), a beta3-adrenoceptor agonist in development for treatment of overactive bladder, two novel HIV-1 non-nucleoside reverse transcriptase inhibitors (antivirals), a dual orexin receptor antagonist, three different cardiovascular drugs (treatment of atrial fibrillation, neutrophil elastase inhibitors), three new cancer drugs (an ALK and ROS1 inhibitor for the treatment of carcinoma, an ERK kinase 1 and 2 inhibitor and a BRAF inhibitor), an endothelin A receptor blocker, two novel factor Xa inhibitors (anticoagulants), a motilin receptor agonist (gastrointestinal), a marketed thyroid hormone, an antiepileptic agent (AMPA antagonist), two novel dipeptidyl-peptidase-4-inhibitors for treatment of type 2 diabetes, a PDE4 inhibitor for treatment of COPD and asthma, a JAK3 inhibitor to treat rheumatoid arthritis, a histamine H1 antagonist, a microsomal triglyceride transfer protein inhibitor, a traded vitamin, a drug to treat electrolyte metabolic disorders, an anticonvulsant clinical candidate (potassium agonist) and two antibacterial drugs (a traded drug inhibiting DNA-dependent RNA polymerase and an investigational peptide deformylase inhibitor).



Current Review article on oral bioavailability in Pharmaceutics 2021:
Drug Screening, Oral Bioavailability and Regulatory Aspects: A Need for Human Organoids.
Zietek T, Boomgaarden WAD, Rath E. Pharmaceutics. 2021 Aug 17;13(8):1280. doi: 10.3390/pharmaceutics13081280. PMID: 34452240 Free PMC article. Review.



Press Release:

IMPACT-F optimizes lead candidates in drug discovery

Pharma companies use the expert system to forecast drug-uptake in humans.

The artificial intelligence technology, developed by PharmaInformatic, Germany, evaluates if a potential drug will be efficiently taken up in humans. IMPACT-F prioritizes drug-candidates based on predicted drug-uptake (“oral bioavailability”). This ranking allows the most efficient drug-candidates to be chosen for further development.

Example: Four drugs of the validation set are ranked on human drug-uptake:


The technology has been used by pharmaceutical companies in therapeutic areas such as diabetes, inflammation, autoimmune diseases, antivirals and cancer. It has been applied to optimize lead candidates and to evaluate oral bioavailability and effective dose prior to human clinical trials. The first drug candidates evaluated with IMPACT-F have now progressed into clinical trials in humans.

Crucially, IMPACT-F improves drug discovery and development at a very early stage, since only the drug structure is needed to reliably forecast oral bioavailability. This enables pharmaceutical companies to focus resources on prospective drug development projects.

Oral bioavailability is one of the most important properties in lead optimisation. A drug must have sufficient oral bioavailability in humans otherwise clinical trials are not effective and drug development is then stopped. Low drug-uptake can result in high inter-individual variability and increases the risk of side-effects and toxicity.

Current Press Release:

IMPACT- F optimizes
lead candidates
in drug discovery



==> selects oral bioavailable

==> increases efficacy of clinical trials

==> results
directly available

Only compound structure needed
==> no further assays, synthesis
 or costs



Absorption Distribution Metabolism Excretion.
Bioavailability combines Absorption & Metabolism

PK Pharmacokinetics

Quantitative Structure
The chemical structure is set in relation to
biological activity.

New Drug

Lead Optimization
Drug discovery starts from
initial hits with pharmacological activity.
Structural modifications of compound structure yield to optimised leads. They can progress to drug candidates, which are investigated in human clinical trials.

 Drug Metabolism and Pharmacokinetics

New Drug Application

Quantitative Structure
Property Relationship


is key property
of leads and

New Chemical Entity

Novel models to forecast
Plasma Protein Binding
of compounds
show a high quality of prediction.

A low error
and high
between experimental and predicted PPB values was found, based on a large independent validation dataset.


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Bioavailability prediction of drug candidates for
treatment of Type 2 diabetes

...and in short time our development project was taken to the next step."



New collaboration:

DoCE Challenge
 (Unilever, Shell)

Sponsored by Unilever and Shell, this challenge aims to develop methods and tools that will better quantify and control the exposure of chemicals for predicting in vivo toxicity.