Technology · APOLLO™ · Program PITO-001

APOLLO™ — the Personalized Injection Treatment Optimizer.

APOLLO™ is the commercial name of PITO — the Personalized Injection Treatment Optimizer — carried internally as program PITO-001. It is one platform: it is designed to determine what an individual patient should receive, and to prepare it at the point of care. Protected by patents granted internationally.

APOLLO™Personalized Injection Treatment Optimizer
PITO-001Internal program code
US 9,675,519Granted 2017
EP 2667965Granted 2016
The architecture

A closed loop between decision and preparation.

The platform both determines the treatment and prepares it, and carries the record forward from one to the next.

The platform produces a recommended personalized treatment and prepares it at the point of care. Each preparation event is recorded to the cloud against that individual, so the record grows richer over time rather than resetting at every visit.

That accumulated history is what makes the follow-up better than the first appointment. A treatment is not a single decision repeated — it is a sequence, and each step should be informed by the one before it.

The intelligence is modular. Each module is a source of evidence the clinician can switch on, weight, or leave out entirely.

PITO-001Personalized Injection
Treatment Optimizer
APOLLO™Preparation &
treatment platform
ArchitectureModular AI
RecordCloud, longitudinal
DecisionClinician's
01
Inputs

The modules the clinician has enabled, weighted to their own practice.

02
Recommendation

A proposed personalized treatment, with the basis available for review.

03
Clinician decides

The physician accepts, adjusts or overrides. Nothing proceeds otherwise.

04
Preparation

APOLLO™ prepares the formulation at the point of care.

05
Record

The event is stored to the cloud against the individual patient.

Each recorded outcome enriches that patient's history — and informs the next recommendation.
The modules

An open-ended set of evidence sources, configured by the physician.

The Big Data engine is not a fixed algorithm. Modules can be added as new categories of evidence become relevant, and each clinician decides which ones inform their practice.

01

Physician's own experience

The clinician's accumulated judgment, weighted as a first-class input rather than treated as noise.

02

Patient-reported symptoms

What the patient actually describes, in their own words, carried into the recommendation.

03

Published literature

Publication data, so a recommendation reflects the current evidence base rather than a fixed rule set.

04

Genetic information

Where available, individual genetic data as an input to formulation and dose.

05

Interactions & side effects

Drug–drug interaction and adverse-effect data screened against the specific patient.

06

Drug comparisons

Comparative data across therapeutic options, surfaced at the point the choice is made.

A design constraint, not a disclaimer

The platform does not replace the physician. The physician's recommendation is itself one of the engine's most heavily weighted inputs.

The clinician configures which modules apply, can review the basis of any recommendation, and makes the treatment decision. The system's role is to bring the relevant evidence to the moment of that decision — not to make it.

APOLLO™

Designed for personalized preparation.

APOLLO™ was conceived to connect physician-directed treatment optimization with the preparation of individualized therapies, including workflows involving reconstituted or compounded aesthetic treatments.

The platform architecture can support physician-directed treatment preparation across a range of injectable and aesthetic applications, allowing intelligence, formulation, delivery and follow-up data to operate as one connected system.

That is what separates the architecture from a recommendation engine. A recommendation that cannot be prepared, delivered and then measured is an opinion. Here each step is connected to the next.

Recommendation
What the patient should receive
Preparation
Made ready for that patient
Delivery
Placed where it acts
Outcome tracking
Recorded, and fed back

Four steps that are usually four separate systems.

Protection

Protected internationally.

The platform is covered by granted patents across international jurisdictions, in a family whose earliest priority date is January 2011.

European protection was granted in 2016 (EP 2667965) and the United States patent in 2017 (US 9,675,519). A continuation-in-part granted in 2018 (US 10,106,278) extends the platform further — additional preparation embodiments, sensor integration, synchronization with a complementary health-management system, and application to topical treatments as well as injectables.

See the selected register

Earliest priorityJan 2011
EuropeEP 2667965
United StatesUS 9,675,519
ExtensionUS 10,106,278