This ‘drug space’ was generated using StarDrop’s drug discovery chemical space visualisation using a set of 1395 marketed small molecule drugs. In this space, the proximity of two points represents the structural similarity between the corresponding compounds. This provides a convenient way to map the distribution of compounds or their properties across the chemical diversity of drugs. The figure below shows some illustrative structures for different regions of the space.
In generating this space, the similarity between two compounds is defined using a Tanimoto index based on a 2D path-based fingerprint. The distribution of points is generated using the t-distributed stochastic neighbour embedding algorithm .
The compound structures used to create the drug space were downloaded from the ChEMBL approved drug list . Only compounds assigned a ‘Development Phase’ of 4 were retained. Duplicate structures and compounds with molecular weight less than 100 Da or greater than 1000 Da were removed.
StarDrop users can download a Drug Space StarDrop Project containing this data set and plot their compounds into the same drug space.
Pharmacokinetics Scoring Profile
Each of the compounds were scored using StarDrop’s Probabilistic Scoring approach  for multi-parameter optimisation. This assesses the overall balance of properties against a profile of criteria representing the desired properties of a high quality compound for the therapeutic objectives of a project. The overall score, between 0 and 1, represents the likelihood of achieving the ideal outcome for all properties.
The ten drugs were scored based on their clinically observed pharmacokinetic (PK) properties:
- Oral bioavailability (%)
- Half-life (h)
- Plasma-protein binding (%)
- Volume of distribution (L)
For each compound, a histogram shows the performance of each of these properties against the desired property values, as illustrated right.
A high bar for a property indicates a good value of the property while a low bar corresponds to a poor value against an important property criterion. The data for each of the compounds, along with references to the sources, are provided in the table in the Data section below.
In some cases, a bar in a histogram is ‘greyed out’ indicating that the contribution of this compound is based on highly uncertain or missing data. For details, please see the table of detailed information for each compound below.
The scoring profile used to compare the ten compounds was as follows:
The range of desired values for each of the properties is shown above, along with the relative importance of each property criterion. However, the criteria are not defined as hard cut-offs, which could draw artificially harsh distinctions between compounds with similar property values near to the boundaries of the desired ranges. Instead, a ‘desirability function’ has been defined for each criterion, relating the value of each property to its desirability. The desirability functions used in this profile are shown below (in each case the desirability function is shown in blue and the histogram shows the distribution of the corresponding property values for the ten neglected diseases compounds):
1Only lowest 5 half-life compounds are shown on histogram for scale. Some compounds have half-life >100 hours.
This scoring profile is included in a Neglected Diseases StarDrop project which StarDrop users can download to score their own compounds, or modify as required.
The choice of a property profile is subjective to some degree, but the rationales for the choice of these desirability functions are as follows:
- For an orally dosed compound, high oral bioavailability is desirable to achieve good systemic exposure. Typically, a value above 50% would be ideal, but below this, the higher the oral bioavailability the better. A value of zero is clearly unacceptable.
- A half-life above 8 hours would be suitable for dosing no more frequently than twice-daily. A half-life below this would increase the likelihood of requiring larger number of doses or a larger dose to maintain a therapeutic concentration. Requiring a higher number of doses increases the risk of poor patient compliance while administration of large doses would require a high therapeutic index. Due to the challenges of supply and compliance in developing nations, less frequent dosing may be desirable and, in some cases, a single dose treatment would be ideal. Hence, longer half-lives are not penalised, despite the risk of accumulation, potentially leading to toxicity.
- High plasma-protein binding reduces the free concentration of a compound; therefore, plasma-protein binding values close to 100% are undesirable. However, very low plasma-protein values are difficult to achieve; therefore, a desired range of less than 90% is defined.
- A volume of distribution above 70L indicates distribution within total body water, hence a value greater than this would be desirable, with an ideal range between 210 L and 350 L, indicating good tissue exposure. A much higher volume of distribution indicates a greater degree of non-specific binding, increasing the risk of toxicity or undesirable pharmacology; therefore, values above 350L are assigned decreasing desirability, with values above 490 L given the lowest desirability.
Of course, there is no single ‘ideal’ pharmacokinetic profile for a drug for a neglected disease; there are variations in the preferred profile for specific diseases and there are certainly exceptions to these ‘rules’.
First Discovered or Approved
Estimated Number of people affected2
Volume of distribution
8 [16 ]
|Chagas disease, Trypanosomiasis,|
|Malaria and Schistosomiasis|
2  
2-22  
These data can be downloaded in a Neglected Diseases StarDrop Project along with the compound structures and scores.
2 According to the World Health Organisation or Wikipedia
3 Assuming a 70 kg patient
4 Not measured due to haemolysis (high in rats and dogs)
5 No IV formulation, therefore absolute bioavailability cannot be determined
6 Administered intravenously
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