Better rules. Better Matches. Faster.

Transplantation Networks

A national-level transplantation network requires powerful, high-performance technology to support efficient and equitable allocations. Afflo’s hyperscale allocation platform scales seamlessly on demand to support thousands of real-time match runs and live offers.
Afflo’s allocation engine reduces non-productive offers and improves both the efficiency and accuracy of organ matches and offers. Our low-code Policy Management Workbench and algorithms built around established medical criteria and policies.

Targeted, Automated Offer Cycle

Afflo's targeted and automated offer cycle facilitates multi-channel, parallel organ offers that reduce non-productive offers and expedite time to transplant, even if a primary offer is rejected.
Afflo uses a larger set of data, filtering, exclusions, and customizable policy rules to ensure offers are a better match from the outset. Because decision-makers have the data they need, valuable time is saved by eliminating phone calls and manual efforts to get missing information about an offer.

More Choice Implementing Matching Policies

Allocation policies evolve as research evolves and Afflo matching algorithms are designed to be easily configured without sacrificing quality using Afflo's Policy Management Workbench. Afflo supports continuous distribution ranking algorithms that provide all waitlisted patients with an overall score, category-based ranking and hybrid matching that facilitates transition from category to continuous distribution ranking. Afflo also implements flexible and user-configurable exclusion and offer decline policy rules.
Afflo makes it easy to incrementally adopt new algorithms and policy changes on a transplant center, geographical or organ-by-organ basis. This reduces the risks associated with rolling out policy changes and promotes innovation and improvements in organ utilization, patient safety fairness and velocity of policy implementation.

High Resolution HLA Data

Afflo’s Matching and Offer Engine implements virtual crossmatch (VXM) algorithms that leverage high resolution allele-specific, alpha-beta, and epitope/eplet level data and policies. This is the highest resolution of HLA data used in any transplant system and is automated and standardized in the organizations and labs that use Afflo.
Afflo's support of high-resolution HLA data improves virtual cross matching, saving time and resources associated with physical cross matching, and supports all patients, including patients who are highly sensitized. When placing organs at a distance, virtual cross match is even more critical to reducing discards and negative outcomes associated with increased risk of graft rejection with positive cross matches.

Simulate and Test Policy Changes Quickly

Using Afflo's Policy Management Workbench, transplant policy experts can quickly maintain, test, update and govern sophisticated matching and ranking policies/algorithms with minimal IT involvement. The Afflo Policy Forge tool lets non-technical users create/maintain transplant center-specific exclusion, ranking and offer decline policy rules.
Afflo's Policy Time Machine feature lets users simulate and analyze proposed policy rule changes using historical allocation data, which means faster policy implementation, improved testing, and fewer unexpected impacts. The Afflo solution is unique in that it saves snapshots of all performed matches to enable historical impact analysis and testing of proposed policy changes.

Electronic Offers on Any Device

We know the waitlist never sleeps. With Afflo, transplant care teams know about matches instantly on any device through our automated electronic offer cycle. Afflo advanced filtering and options ensures its notifications are always directed and precise, it simplifies the noise transplant centers deal with.

Improved Compliance and Auditing

Afflo’s modularity and automated documentation captures policy rules and algorithms in a technology-independent way so that users can audit and communicate policy. Automated documentation, including data dictionaries, means knowledge transfer, auditability, and compliance are enabled—not encumbered—by continuous improvement initiatives.