Evidence map›Paper›PMID 34294862›Full record

ArticleCommunications biology2021

Development of a mechanistic model to predict synthetic biotic activity in healthy volunteers and patients with phenylketonuria.

Mark R Charbonneau, William S Denney, Nicholas G Horvath, Pasquale Cantarella, Mary J Castillo, Marja K Puurunen, Aoife M Brennan

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Engineered probiotics.Microbial cell factories · 2022
    Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Mark R CharbonneauSynlogic, Inc., Cambridge, MA, USA. mark@synlogictx.com.ORCID 0000-0003-4893-8244
William S DenneyHuman Predictions, LLC, Cambridge, MA, USA.ORCID 0000-0002-5759-428X
Nicholas G HorvathSynlogic, Inc., Cambridge, MA, USA.
Pasquale CantarellaSynlogic, Inc., Cambridge, MA, USA.
Mary J CastilloSynlogic, Inc., Cambridge, MA, USA.
Marja K PuurunenSynlogic, Inc., Cambridge, MA, USA.
Aoife M BrennanSynlogic, Inc., Cambridge, MA, USA.
Synlogic (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of therapeutics depends on predictions of clinical activity from pre-clinical data. We have previously described SYNB1618, an engineered bacterial therapeutic (synthetic biotic) for the treatment of Phenylketonuria (PKU), a rare genetic disease that leads to accumulation of plasma phenylalanine (Phe) and severe neurological complications. SYNB1618 consumes Phe in preclinical models, healthy human volunteers, and PKU patients. However, it remains unclear to what extent Phe consumption by SYNB1618 in the gastrointestinal tract lowers plasma Phe levels in PKU patients. Here, we construct a mechanistic model that predicts SYNB1618 function in non-human primates and healthy subjects by combining in vitro simulations and prior knowledge of human physiology. In addition, we extend a model of plasma Phe kinetics in PKU patients, in order to estimate plasma Phe lowering by SYNB1618. This approach provides a framework that can be used more broadly to define the therapeutic potential of synthetic biotics.

Indexed as

Healthy VolunteersAnimalsHumansPhenylketonuriasPrimates

Identifiers

PMID34294862
PMCPMC8298439
OpenAlexW3184613767

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.